Do the following sound familiar?

• Dad, I can follow the lesson video on my computer while playing on my phone.
• I am listening to you, honey! I just need to send this email.
• Yes, I totally agree! But could you repeat what you said one more time, please?

Yes, these are common aspects of our daily conversations. Many go through life assuming they are “intelligent” enough to juggle multiple tasks at once, while others constantly race against time, trying to complete as many chores as possible—almost as if there were an ultimate finish line. “Multitasking” has unfortunately become so widespread despite all the scientific evidence that the human brain is not wired to handle multiple tasks simultaneously. A cursory search on the Internet would present the unequivocal conclusion that what we do in these instances is not actually “multitasking,” but rather “task-switching.” As with any situation where we act against our innate nature—designed with purpose—dysfunctions arise, setting off a chain reaction that affects many aspects of life.

What happened to the age-old advice that parents should spend “quality time” with their children, giving them their full attention? Has the importance of establishing and maintaining eye contact in a conversation diminished? Have we come to cherish being constantly chased by time, burdened with endless tasks imposed on us, rather than taking control and steering it toward the goals we truly value? These are just a few of the many questions we, as human beings, need to ask ourselves to reset our lifestyles, striving to have meaningful, peaceful lives worthy of living with admirable outcomes.

What happens if we don’t rectify our lifestyles? How much does “multitasking” chip away from our personal, social, and professional lives? Let’s start with our personal lives. If we strive to do things the right way by giving them the time and attention they deserve, then “multitasking” becomes a source of stress, as we constantly struggle to keep up with multiple tasks at once without overlooking anything. This very reason is also highly likely to generate anxiety since we worry whether we are doing things correctly and completing them as expected. Finally, if we spend most of our time juggling small tasks that require different types of activities and lead to diverse outcomes, we end up undermining our ability to focus on a single, more comprehensive task—one that demands a much longer period of concentration than needed for our “multi tasks.” It is well known that stress, anxiety, and low concentration trigger a chain reaction of physical conditions, including elevated blood pressure and increased heart rate, and contribute to a long list of illnesses.

Let’s continue with our social lives. Here is a common scene in today’s families, the innermost circle of social life. Family members sit together in the same living room, each absorbed in their phones, scrolling through social media posts that have no relevance to their own family. Everyone is immersed in their own “alternative world,” disconnected from real life, spending all their time ensuring they don’t miss a single detail of others’ lives. Meanwhile, they may overlook a child’s genuine need for attention and care from their parents. The entire interaction consists of a few brief moments of superficial communication that lead nowhere. Each person is left to experience their own joys and sorrows alone, making their own decisions without support. Over time, this erodes the bonds of love and respect within the family. Doesn’t this resemble a chain reaction, like the one that leads to an atom bomb exploding within the family?

Now, let’s turn to the outer circle of social life: friends. When gathered together, only a couple of friends actually listen to the one speaking, while the rest are absorbed in their phones. Then, they switch roles—the ones who were distracted start talking, while the others retreat into their screens. A series of fragmented conversations unfold, each failing to reach a conclusion and, as a result, depriving us of the cognitive joy that comes from a sense of wholeness or completeness. In other words, it becomes a hodgepodge of collective monologues, where no one is truly trying to understand one another. Instead, they speak just for the sake of talking, mistaking this for “socializing with good friends.” No one is giving the attention needed to fully understand a topic of conversation and everything spoken is forgotten the minute goodbyes are said. Once again, love, respect, and care among these so-called “true friends” begin to fade, weakening the bonds essential for building and sustaining a close-knit circle of friendship.

One might assume that professional life is the one domain where multitasking proves valuable. After all, productivity and task completion are what matter most in the workplace. Surely, multitasking would support these goals, right? Unfortunately, that is not the case. On the contrary, in addition to its three common effects in personal life—stress, anxiety, and low concentration—multitasking triggers chain reactions that can significantly harm the workplace climate and productivity. Let’s begin with the most commonly expected “benefit” of “multitasking”: productivity. A quick internet search reveals studies showing that when employees are unable to focus on a single task for ten minutes, twenty minutes, or thirty minutes because they have to answer phone calls or attend to clients at the same time, companies suffer significant losses in productivity.

A more subtle consequence in the workplace arises when an employee, overwhelmed by the pressure to multitask, abandons their quality standards and “takes the liberty of” making abundant mistakes. In most office environments, these mistakes do not go unnoticed by colleagues. They eventually have to be corrected by these colleagues, creating extra workload for them. When this pattern persists, it inevitably creates tension among colleagues and disrupts an otherwise warm and cooperative work environment. One does not need to be a fortuneteller to predict what kind of a domino effect such tension would have on the harmonious functioning of such a workplace.

To conclude, after reflecting on the so-called virtues of multitasking, the choice is yours—struggle with constant fragmentation or find peace of mind by focusing on one task at a time.

Human beings are visually-oriented in their daily life; they use the sense of sight more than any of the other senses with which they have been endowed. The modern understanding of human vision and the underlining principles were only discovered in the past couple centuries. The nineteenth and twentieth centuries witnessed the development of photographic and digital imaging camera systems, which partially mimic human visual systems. We will open a small window on the history of human vision and camera systems, and try to compare today’s state-of-the-art cameras with the human visual system, focusing mainly on solid-state image sensors, or camera chips, and the image-sensing element of the human visual system, the eye.

History of human vision

Human vision has been the subject of conflicting interpretations since ancient times. Many ancient physicians and philosophers believed in the theory of extramission, or the active eye. According to this theory, the eye perceives objects by emanating light and seizing objects with its rays. It was in medieval Islamic culture that research on human vision and optics developed into a system similar to the modern theory of vision. Among others, Ibn Al-Haytham (Alhazen) (965-1040 A.D.), a Muslim physicist, astronomer, and mathematician in the tenth century, played a great part in this field by promoting the intromission theory which states that vision only occurs because of light rays entering the eye. Ibn Al-Haytham founded physiological optics, which distinguished the functioning of the eye from the behavior of light. On the other hand, ten centuries after Ibn Al-Haytham, Winer et al. (2002) have found recent evidence that as many as 50% of American college students believe in the extramission theory.1

Although the fundamental features, anatomy, and physiology of the eye were documented by Galen (129–200 A.D.), an ancient Greek physician, in the second century A.D., it was Kepler, a close reader of Ibn Al-Haytham, who offered the first theory of the retinal image and the correct operation of the eye in 1604. He proclaimed, “Therefore vision occurs through a picture of the visible things on the white, concave surface of the retina.” Progress came slowly after Kepler, because little was known about the nervous system until the nineteenth century, and only recently have scientists acquired a more knowledge about how the brain apprehends the retinal image. But many questions still elude us.

History of the camera

In parallel with curiosity about human vision, human beings have also tried to mimic human vision by capturing images of objects with instruments. Around 1000 A.D., Ibn Al-Haytham, also known as the father of modern optics, invented the pinhole camera,2 and explained why the image was upside down. It was Johannes Kepler who further suggested the use of a lens to improve the pinhole camera in the 1600s. Capturing an image on a photographic plate was first achieved in the early 1800s. Consequently, photographic cameras began to be mass-marketed in the twentieth century. The photographic equipment with which we are all familiar today, such as the 35mm camera, flash bulb, Polaroid camera, and the point-and-shoot auto focus camera, all were developed in the twentieth century. The invention of the camera as we know it today paved the way for other technologies, including the moving image capture, and, later, the digital camera, in which electronic image-capture devices were used. In 1972, chemically processing an image onto photographic paper no longer became the sole destination of an image, because the first filmless electronic camera was patented by Texas Instruments Corporation. Filmless electronic cameras were made possible with the invention of solid-state image-capture devices called charge coupled devices (CCD) and metal-oxide-semiconductor (MOS) image sensors in the late 1960s. Since the invention of solid-state imagers, people have become more visually stimulated and oriented than ever before in history.

A comparison of camera chips and the human eye

The technological advancements of solid-state image-capture camera chip design and manufacturing during the past twenty-five years has made digital imaging more affordable and accessible to the general public. These advancements have become more visible to consumers in mobile products, particularly in cellular phones, in which there are still and video-camera functions. Although digital cameras are easily available today, the state-of-the-art image sensor chips used in these cameras exhibit a performance gap when compared with the capabilities of the human eye. How good these image sensor chips are today when compared to our eyes is a question that will be elaborated on.

It is possible to compare the capabilities of the human eye and state-of-the-art image sensor chips used in cellular phones or in mainstream PC and digital still cameras. It is also possible to compare the capabilities of the human visual system, including the eyes, the optic nerve, the visual cortex, etc. with a digital camera system which includes optics, image-capture and signal-processing chips and other camera apparatuses. The capabilities include ability to see different colors (spectral response), photo-element (pixel) characteristics (size, density, distribution), light sensitivity, light-intensity response range, functionality and operation modes, and signal processing capabilities.

Spectral response

A single light-sensing element in a solid-state image sensor is called a pixel. In the human eye it is called the photoreceptor. Both elements convert impinging light or photons into electrical signals. The human eye sees in the so-called visible spectrum, between 380nm (blue) and 750 nm (red), and utilizes two kinds of photoreceptors on the retina; rods and cones. The cones are used for color and daylight vision. Rods are responsible for night vision. There are three types of cone photoreceptors on the retina that contain different types of photosensitive pigments. The three types of cones are L, M, and S, and they have pigments that respond best to wavelengths of light that are long or red (peak at 564 nm), medium or green (peak at 534 nm), and short or blue (peak at 420 nm), respectively. The rods (R) are most sensitive at a wavelength of approximately 498 nm (green), as seen in Figure 1.3 Image sensor pixels in digital cameras mimic the photoreceptors in the human eye for color vision. They utilize three kinds of color filters (red, green, blue) on top of each pixel to convert light rays into electrical signals in different visible spectrums. Unlike the cones in the human eye, camera pixels and color filters can be designed to cover wide spectrums that are not visible to the human eye, for instance, the x-ray, ultraviolet, and infrared spectrums. In the category of spectral response range, camera pixels exhibit greater flexibility than those of the photoreceptors of the human eye. On the other hand, interestingly enough, the eyesight that humans possess has similar spectral characteristics as the sun. The solar light emission peaks in the visible spectrum as seen in Figure 2.4

Figure 1. Spectral absorption curves of the short (S), medium (M), and long (L) wavelength pigments in human cone and rod cells.3

Figure 2. The daylight solar spectral power distribution on earth.4

Pixel and array size

The size of pixels in today’s modern digital cameras is getting closer to the size of the photoreceptors in human eye. The typical human eye contains an average of 130 million photoreceptors. The diameter of the rods and cones varies between 1.0m and 8.0m, depending on their location on the retina.5 Today’s state-of-the-art image sensor chips contain 10 to 30 million pixels. Each pixel can be as small as 1.4m in diameter. To date there has been no image sensor that is 1.4m pixel in size or more than 8 million pixels. However, the human being has been equipped with photoreceptors that are as small as 1.0m and has more than 100 million photoreceptors; and this is since the beginning of existence. It is also estimated that the resolution of the human eye is equivalent to an imager sensor chip of 576 million pixels with a 120 degree field of view.6 Thus we still have a long way to go in improving the image-sensor pixel and array sizes used in cameras if we are to match the human eye.

Pixel distribution and formation

In the human eye the photoreceptor size and densities change, depending on their location on the retina. For example, no rods exist on the focus center of the eye, which is called the fovea. Color vision photoreceptors, which total only 10% of the eye’s photoreceptors, are located mostly on the fovea. There is an irregular distribution of photoreceptors which is unique for every human being, like a fingerprint. Yet, we all see things the same, such as colors (with the exception of people who are colorblind). In camera chips, however, pixels are arrayed regularly, in two-dimensions. As the image-processing techniques and algorithms used in camera systems are linear and do not closely mimic the signal processing that exists in the human visual system, regularly arrayed pixels are required.

Light sensitivity and response range

Although the pixel sizes in image-sensor chips are approaching the size of the photoreceptors in the human eye, camera systems are not yet close to being able to match performance in terms of light sensitivity and response range. The human visual system and photoreceptors can easily adapt to very dim and bright light, with a light-intensity response range of ten billion to one (1010:1).7 This response range goes from light conditions on a bright sunny day to dim night vision. Typically, a conventional consumer camera pixel has a light intensity response range of one thousand to one (103:1).8 In a camera system, details of a captured scene are either concealed in the dark regions or washed out by the bright light, depending on the exposure settings of the system. Thus, one could say that the human visual system works ten million times (107) more efficiently than that of consumer cameras in terms of transferring scenes into images.

Operation principle

In terms of operation principles, the photoreceptors in the human eye convert light rays into electrical signals with extremely rapid electro-chemical reactions which can detect a single photon. Typically, in the image sensor pixel of a digital camera the photoelectric effect is used to convert impinging photons into electrical charges. Electrical charges are collected and stored in each pixel during the exposure period. Collected electric charges in each pixel are amplified and converted into digital ones (logic-1) and zeros (logic-0) during image readout before the image is sent to higher processing elements, such as a personal computer, digital-still or video camera. It is possible for a single photon-counting camera to be developed. However, very special and larger pixel sizes and extra apparatuses are required to build such a camera system. Thus, we could say that it is almost impossible to build imaging pixels that have the capability and dimensions of the photoreceptors of the human eye with today’s state-of-the-art technology.

Signal processing capabilities

The captured image in the human eye is preprocessed before it is sent to the visual cortex of the brain. This preprocessing consists of a data reduction operation in which nothing is lost, with a compression ratio of 130 to 1, as only 1 million optic nerves leave each eye carrying the information from 130 million photoreceptors. This compression allows the brain to process information at a rate of 25 to 150 scenes or frames per second. Typically, every pixel in an image sensor chip is first transferred to higher processing units. A data compression method is either carried out with some loss of details in the image or the compression is never used. The transfer of frames in camera chips typically takes place sequentially, reducing the speed of the image-capture operation or frame rate. Different techniques are used to maintain a capture rate of, at most, 25 frames-per-second in camera chips. With today’s technology, image sensors that have a capture rate of one million frames per second have been proposed and can be manufactured for scientific applications.

The inherent inefficiencies of image-capture in today’s image-sensor chips are hidden by employing the limitations of the human eye. For example, solid-state image sensors have always been produced with row or column-vice uncanny stripes which are easily picked up by the human eye. However, psycho-visual experiments have shown that the human eye can only detect contrasts between two adjacent gray lines when the difference is greater than 0.5%. Thus, if a camera chip is designed to have a column to column or row to row contrast of less than 0.5%, these odd stripes would not be visible.

Conclusion

Humans are visually oriented and without a doubt, our eyes are considered to be our primary source of information. It is obvious that the human visual system is extremely complex and this complexity has fascinated human beings throughout history. Yet, the underlining principles and basic functions of human vision and the eye have only been discovered during the last two centuries. These discoveries have led research in how to mimic these functions, which has resulted in moving and still-photographic and camera equipment, and the image sensors chips used in digital cameras today. Even though human beings are only taking baby steps in fully mimicking the human eye, curiosity and scientific inquiry allows us to discover functions and features of the eye and the visual pathways that will increase our knowledge and help us to build better pixels and image sensor chips.

References

1. Winer, G. A., Cottrell, J. E., Gregg, V., Fournier, J. S., & Bica, L. A., “Fundamentally misunderstanding visual perception: Adults’ beliefs in visual emissions.” American Psychologist, 57, 417-424, 2002.

2. Ertan Salik, “Pinhole Cameras, Imaging, and The Eye” The Fountain Magazine, Issue 54, pp. 30-33, April – June 2006.

3. URL: http://en.wikipedia.org/wiki/Image:Cone-response.png

4. URL: http://www.handprint.com/HP/WCL/color3.html

5. Stefan Winkler, Digital Video Quality – Vision Models and Metrics, John-Wiley & Sons, Ltd., 2005.

6. URL: http://www.clarkvision.com/imagedetail/eye-resolution.html

7. R.C. Gonzalez and R.E. Woods, Digital Image Processing, Addison-Wesley, 1993.

8. M. Schanz, et al., “A high-dynamic-range CMOS image sensor for automotive applications”, IEEE Journal of Solid-State Circuits, vol. 35, no. 7, pp.932-938, July 2000.

WHY OPTICAL?

Despite the many benefits that classical computers (‘classical’ here means computers in which the signals are carried electrically) have brought to our lives, they have some limitations which prevent any improvement in the speed or volume of signals carried. These limitations are inherent to the way these computers work.

For example, classic electric circuits carry information units serially, one by one, and there are some lower limits beyond which such circuits cannot be built-below that limit they simply cannot process the information reliably. Another handicap is that electrons floating in circuits can interfere with each other-and this interference, incidentally, is one reason why engineers cannot produce smaller circuits. By contrast, photons, light particles, which are the main signal or information carrying agent simply do not interact with each other because they do not carry a charge.

An optical computer could be run faster than one running electrons, theoretically at the speed of light, along optical fibres which are specifically designed guide-wires to transfer light-photons in and out between chips in an optical computer without distortion.

One of the main advantages of optical computers is their capability of processing more than one piece of information at the same moment. That means multi-beams can be processed in one chip. This would allow engineers to use parallel processing which greatly enhances the speed of the computer.

THE DIFFICULTIES

Lasers would, naturally, be the source of light in this new generation of computers. Scientists and engineers all over the world are trying to build appropriately tiny lasers emitting precise frequencies of infrared light. But they face a number of practical hurdles. One has to do with making lasers of appropriate size and efficiency. Current technology does not have the means to build optical chips comparable in size to ‘classical’ ones. The efficiency of the lasers is not high enough for the specifications required. Most of the energy to run these lasers escapes as heat and is not used. Since one or at most two percent of this energy can be transformed into the useful form of light, the rest can generate a lot of heat which is dangerous to the condition of the chips.

Making the right lasers is not the only problem on the way to fully optical computers. Switches are at the heart of optical computers, but as photons do not interact with each other, there are substaintial difficulties in building switches.

SOME PROPOSED SOLUTIONS

One solution to this problem is to build computers which are part electrical, part optical. Many scientists now believe that the most viable use for optical technology is in this type of hybrid system combining optics and electronics. Researchers are now focusing their work on optical interconnections between chips, which could be a reality in as little as one or two years. This type of connection can vastly increase the amount of data moving in and out of chips.

Such a machine would have to contain prisms, mirrors, and lasers to channel the light, as well as gallium arsenide chips that convert pulses of laser light into electrons so as to function as switches. If all this does happen, there will be a need for new computer architectures, that is, new computer structures.

However, there are some scientists following a different route. They are trying to find ways to use current transistor technology so as to detect laser beams in the information processing. NPN type transistors without a metal cover would be appropriate because they are faster. This approach also allows for adaptation of existing designs, with all the advantages in time and savings that brings.

FUTURE

The first optical processor developed at AT&T Bell Labs measured about two feet by two feet. Scientists hope some day to fit it all into three square inches. A fully optical computer is more than five years away.

Scientists have set themselves a target for the year 2000: 1,000 I/O (input and output) channels running at 1 giga-bit/sec. That is a thousand times faster than current modern computers.

It is a pity that we must wait for a decade, while scientists and engineers try to accomplish this difficult task. But what an exciting wait!

•  FURTHER READING
• ‘Bright future’, Scientific American, May 1990.
• ‘Now easier optical’, Electronics, May 1990.
• ‘Slacken lights up’, Scientific American, July 1991.
• ‘Optical computer no longer lighters away’, Byte, April 1992.
• ‘Optical computing sheds ‘blue sky’ image’ Electronics, April 1990.