Chapter I, Digital Imaging Fundamentals: Lesson II Capture http://www.kodak.com/country/US/en/digital/dlc/book3/chapter1/digFundCapture1.shtml

A basic image capture system contains a lens and a detector A basic image capture system contains a lens and a detector. Film detects far more visual information than is possible with a digital system.

With digital photography, the detector is a solid state image sensor called a charge coupled device...CCD for short.

On an area array CCD, a matrix of hundreds of thousands of microscopic photocells creates pixels by sensing the light intensity of small portions of the film image.

To capture images in color, red, green and blue filters are placed over the photocells.

Film scanners often use three linear array image sensors covered with red, green and blue filters.

Each linear image sensor, containing thousands of photocells, is moved across the film to capture the image one-line-at-a-time.

Other types of scanners are drum scanners, flatbed scanners and document scanners.

Drum-scanners are high-end scanners used by the printing industry Drum-scanners are high-end scanners used by the printing industry. They use photomultiplier tubes as detectors - a technology different from the image sensors we will be considering.

Flat bed scanners used for capture of drawings and documents, and high speed document scanners use CCD detectors much like film scanners.

As we learned in Module 1, the quality of a scanned image is determined by pixel size, or spatial resolution; and by pixel depth, or brightness resolution.                              This relates to the two basic steps in the digital capture process: In step one, sampling determines pixel size and brightness value. In step two, quantization determines pixel depth. When a scanner samples the photographic image, it divides the image into pixels. The size of pixels depends upon the number of photocells.

                             This is an example of a CCD with few photocells, samples at low resolution. At extremely low resolution, pixels can be seen with the unaided eye. This is called pixelization.

This is an example of a CCD with more photocells, it samples at higher spatial resolution. In this kind of image individual pixels can no longer be seen.

In a scanner using a matrix of photocells, vertical and horizontal resolution are sampled at the same time.

In a scanner using a linear array, vertical resolution is determined by the size of the photocell. Horizontal resolution is determined by the rate at which the CCD moves across the image. For example, a film scanner can use linear CCDs to sample 2048 photocell sites, as it moves along 3072 lines.

The process by which the CCD converts film images into electronic images is called photoelectric conversion.                             

This brings us to the second step in digital capture, quantization. In a scanner using a matrix of photocells, vertical and horizontal resolution are sampled at the same time.

The more bits the analog-to-digital converter can process, the more digital values it can represent. An 8-bit converter represents 256 brightness levels. A 12-bit converter represents over 4000 brightness levels. The ADC compares the analog input signal to a reference voltage. A lookup table in permanent memory then maps this input value to a digital output.

In a color image, each pixel is assigned three 8-bit numbers for the red, green and blue brightness values. For example, this pixel is created by assigning a red brightness level of 227, a green level of 166, and a blue level of 97.

In addition to spatial and brightness resolution, other factors influencing the quality of a scanned image are dynamic range, noise and artifacts. Dynamic range indicates how well the scanner can differentiate between light levels. Film excels at distinguishing small changes in light level, while digital capture systems have limited brightness range. To accurately render highlights and shadows, scanner exposure must be controlled precisely. With low dynamic range, shadows lose detail and saturated areas are washed out.

Noise is another factor Noise is another factor. The information captured by a sensor contains both image data and noise. Noise appears as small, random variations in brightness or color.

Sensor sites with low signal-to-noise ratio, introduce noise. Sensor sites with high signal-to-noise ratio represent the image accurately.

Artifacts, another factor in digital image capture, are distortions, such as the moiré pattern that occurs when an image is undersampled.

The sampling rate should be based on the spatial frequency of the image. Spatial frequency is the rate at which the brightness of the image changes. For example, the teeth in this photo show slow changes in brightness levels, or a low spatial frequency. The hair shows rapid changes in brightness levels, or a high spatial frequency.

To eliminate moiré in this photo, the sampling rate should be twice as high as the spatial frequency of the hair. In other words, pixels should be small enough so that each detail is represented on two pixels.

Lesson Review Let's review what we've just learned. Select 1 or 2 on the image to indicate which image capture process determines pixel size, or spatial resolution.

Lesson Review 2 Let's review what we've just learned. Select 1, 2, or 3 on the image indicate which type of image quality problem this represents.