Essential Principles of Image Sensors

Takao Kuroda

• Publisher: CRC Press
• Year: 2017
• Print ISBN:
  9781482220056
• eBook ISBN:
  9781351831307
• Topic: Technology & Engineering
• Subtopic: Electrical Engineering & Telecommunications
• Index: Technology & Engineering

Providing a succinct introduction to the systemization, noise sources, and signal processes of image sensor technology, Essential Principles of Image Sensors discusses image information and its four factors: space, light intensity, wavelength, and time. Featuring clarifying and insightful illustrations, this must-have text:

• Explains how image sensors convert optical image information into image signals
• Treats space, wavelength, and time as digitized built-in coordinate points in image sensors and systems
• Details the operational principles, pixel technology, and evolution of CCD, MOS, and CMOS sensors with updated technology
• Describes sampling theory, presenting unique figures demonstrating the importance of phase
• Explores causes for the decline of image information quality

In a straightforward manner suitable for beginners and experts alike, Essential Principles of Image Sensors covers key topics related to digital imaging including semiconductor physics, component elements necessary for image sensors, silicon as a sensitive material, noises in sensors, and more.

1
Task of Imaging and Role of Image Sensors

Various kinds of instruments such as digital still cameras (DSCs), camera phones, and camcorders allow us to enjoy personal images. Moreover, broadcasting cameras, which provide high-definition images, are indispensable to the television industry. Not only are there cameras for personal enjoyment, but there are also cameras for other applications such as for automobiles and security systems, and endoscopes for medical use. Cameras are not only used for visible light, but they are also used for thermography, which visualizes thermal distribution by infrared imaging; there are also cameras for ultraviolet and x-ray imaging. In addition, there are cameras that capture very-high-speed phenomena and cameras that obtain highly accurate color information. Furthermore, there are cameras whose images are used not by the human eye but by machines, such as cameras for automated driving and machine vision, which judge information obtained from images. As just described, various kinds of cameras are utilized in a very wide range of fields.

Why are there so many kinds of imaging systems as typified by cameras? The reason is to obtain images with adequate image quality for the purpose of each imaging system. In each imaging system, the role of each image sensor is to pick up image information of high enough quality for that system.

In this chapter, the factors that determine image information are confirmed. Then, the structure of image sensor output and image information are set out. Unless explicitly stated otherwise, the explanations are based on “almost all image sensors” (see Section 1.2.3). Concerning the terms used in this book, image information is used for image information in a broader sense, optical image information is used for information contained in optical images, and image signal is used for image sensor output obtained from optical images.

1.1 Factors Constructing Image Information

What is image information made up of? For the sake of simplicity, let us initially focus on a monochrome still picture. There is a concentration distribution of black and white in two-dimensional space in a monochrome still picture. The concentration indicates the light intensity, which is brighter at lower concentrations. That is, the concentration is the light intensity distribution at each position in two-dimensional space. Therefore, an image is constructed using the information on space (position) and the intensity of the light at that position.

Let us now consider color still images. Since information on the wavelength of light must be added, color image information is formed by light intensity, space, and wavelength. Moreover, in the case of color moving images, time information when light reaches the image should be added. Thus, the image information is composed of four factors: light intensity, space (position), wavelength, and time.¹

Among these factors, space has two dimensions, however wavelength information is often replaced and approximated by the primary colors red, green, and blue, as will be shown later; therefore, color can be considered three dimensional and time has one dimension. Thus, as shown in Figure 1.1, a distribution of the four factors in seven dimensions, that is, a set of each of the coordinate points of light intensity, space, wavelength, and time constructs the image information.

The indexes that indicate the level of information quality are accuracy and range, as shown in Figure 1.2. While the accuracy of value is the resolution capability, which means the signal-to-noise ratio (SNR), the range is the extent of the signal information that the imaging system can pick up. Information captured with high accuracy and over a wide range is high-quality image information. In the case of light intensity, for example, the information quality is decided by the level of SNR and the dynamic range, which decribes the maximum and minimum measurable light intensities that the imaging system can capture, as shown in Figure 1.3.

Figure 1.1

Structure of optical image information.

Figure 1.2

Quality of image information: Accuracy and range.

FIGURE 1.3

(See color insert) Example of the quality of light intensity information.

The accuracy and range of the four factors are shown in Table 1.1. The accuracy of space information is space resolution, that of wavelength is color reproducibility, and that of time is time resolution. The ranges of space,^* wavelength, and time are the capturing space range, the color gamut or wavelength range, and the storage time range,^† respectively. Apart from special applications and the dynamic range of intensity, these ranges are rarely a problem.

In addition to intensity and wavelength, polarization and phase are among the light conditions. Although these are not discussed in this book, some examples deal with this information, such as sensors to obtain the polarization distribution,² which concerns the surface conditions of materials and textured surfaces, and sensors³ and systems⁴ to obtain depth and range information using phase difference.⁵ There is a sensor⁶ that gets range information from the angle information of incident light. Since there is a strong need for information on range and depth, progress in this field is expected.

Table 1.1

Accuracy and Range of Four Factors

^* Although space is directly related to the sensor size, it can be extended by using a wide lens such as a fish-eye lens.

^† Storage memory size.

1.2 Image Sensor Output and Structure of Image Signal

In this section, the structure of an image signal captured by image sensors is discussed.

1.2.1 Monochrome Still Images

As discussed in Section 1.1, the only image information required for monochrome still images is light intensity and space (position). The basic device configuration of image sensors is shown in Figure 1.4. Image sensors have an image area on which optical images are focused and are converted to image signals for output. In the image area, unit cells called pixels are arranged in a matrix in a plane. Each pixel has a sensor part typified by a photodiode, which absorbs incident light to generate a certain quantity of signal charges according to the light intensity. Thus, the light intensity information for a pixel is obtained at each sensor part. Figure 1.5b shows a partially enlarged image of Figure 1.5a, and the image signal of the same area captured by image sensors is shown in Figure 1.5c. The density of each rectangular block is the output of each pixel and the light intensity information S(x_i, y_j) at the coordinate point (x_i, y_j) of each pixel. Expressing a two-dimensional coordinate point (x_i, y_j) using r_k, ...

Table of contents

• Cover Page
• Title Page
• Copyright Page
• Table of Contents
• Preface to English Edition
• Preface to Japanese Edition
• Author
• 1 Task of Imaging and Role of Image Sensors
• 2 Device Elements and Circuits for Image Sensors
• 3 Major Types of Noise in Image Sensors
• 4 Integration Period and Scanning Mode
• 5 Types of Image Sensors
• 6 Impacts of Digitization by Built-In Coordinate Points on Image Information Quality
• 7 Technologies to Improve Image Information Quality
• 8 Imaging Systems
• Epilogue
• Index