Digital Imaging and Image Analysis

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Presentation transcript:

Digital Imaging and Image Analysis Bozzola and Russell – Chapter 18

A black and white photograph is nothing more than a two dimensional arrangement of black (silver grains) and white (paper backing from which grains have been removed) arranged in such a way that they create an image.

Image Processing: Optical: Mechanical manipulation (lenses, enlargers, etc.) Analog: Electronic manipulation Digital: Computer manipulation: Image as a data matrix

Image Processing: Optical: Brightness, contrast, enlargement, cropping, dodging & burning Analog: Digital:

Image Processing: Optical: Brightness, contrast, enlargement, cropping, dodging & burning Analog: Brightness, contrast. Digital:

Image Processing: Optical: Brightness, contrast, enlargement, cropping, dodging & burning Analog: Brightness, contrast. Digital: Brightness, contrast, enlargement, cropping, dodging & burning, non- linear display, contrast stretching, erosion & dilation, edge enhancement, etc.

Contrast vs. Brightness Brightness: The location of a visual perception along the black to white continuum Bright Dark

Contrast vs. Brightness Contrast: The range of optical density and tone on a photographic image (or the extent to which adjacent areas on a CRT differ in brightness. High Low

Contrast vs. Brightness As contrast is increased the overall brightness of the image appears to increase in some areas and decrease in others

In photographic image processing brightness is modified by exposure which is a function of illumination intensity X time. The longer the time and/or the more intense the illumination the brighter the image will be. In analog processing brightness is increased by increasing the signal going to each pixel In digital processing brightness is increased by increasing the numerical value of each pixel by an equal amount.

In photographic image processing contrast is controlled by the size of silver grains in the emulsion, the larger the grains the greater the contrast. In analog processing contrast is increased by varying the ranges of signal to each pixel. In digital processing contrast is increased by expanding the differences in numerical values between the maximum and minimum pixels.

Image Processing: Optical: Stored as negatives (original) or prints (second generation) Analog: Stored as video (original) or copy (second generation) Digital: Stored as computer data file (original and multiple copies all first generation)

Image Processing: Optical: Transmitted by distribution of prints (second generation) or publication (fourth generation) Analog: Transmitted by distribution of video tapes (second generation) or broadcast (third generation) Digital: Transmitted by file copying and transfer (all first generation)

Digital Imaging: A digital image is nothing more than a data matrix that assigns both a value and a location to each picture element (pixel) in the image

Digital Imaging: When considering the “resolution” of a digital image we need to consider both of these aspects; value of the pixel and its position in the data matrix

Digital Imaging: “Spatial” resolution is defined as the number of pixels used to create the image or more simply the total number of pixels in the matrix.

Spatial Resolution: 100 x 200 25 x 50 13 x 25 3 x 6 Pixel resolution is typically given as X x Y

Spatial Resolution: 100 x 200 25 x 50 13 x 25 3 x 6 More is BETTER!

A digital image from a typical SEM or TEM is often 2K x 2K format whereas a photographic negative from a TEM is closer to 8K x 6K if one were to count silver grains as pixels.

Pixels vs. Dots per Inch Pixel resolution refers to the number of pixels that comprise the image regardless of how large the image is. A typical computer monitor has a 1024 x 768 pixel resolution whether it is a 15” or 21” Dots per Inch or “DPI” refers to the number of pixels per linear inch in the final image. Thus the DPI of a given image decreases as the size of the final image increases.

Digital Imaging: “Grey level” resolution refers to the range of values that each pixel might have. The greater the value range, the greater the grey level resolution.

Grey Level Resolution: Bit = a unit of binary information either a “0” or a “1” Byte = a string of eight bits KiloByte = 1000 Bytes or 8000 bits MegaByte = 1000 KB

Grey Level Resolution: One bit can code for only two values or states (0) or (1) Two bits can code for four states: (0,0) (0,1) (1,0) or (1,1) Three bits for eight and so on.... One Byte can code for 28 or 256 different states (0,0,0,0,0,0,0,0) (0,0,0,0,0,0,0,1)...

This is often referred to as the “bit depth” of an image and it limits the range of pixel values that can be displayed in the image. 1 8 24

Shades of Grey The average human eye can perceive fewer than 100 different shades of grey between absolute white and absolute black. Thus an 8-bit image, with a possible 256 different levels of grey is more than sufficient to display any typical B&W image.

Range of Color: Color digital images can also be based on 8-bit format but in this case a total of three separate pixels (Red, Green, & Blue) are combined for a 24 bit-depth range of colors. 28 x 28 x 28 = 224 = RGB 16,777,216 different colors

The best digital capture devices are capable of capturing images in 12 or even 16-bit (216) grey scale format and are cooled to reduce the effects of noise from the electronics. Micro Luminetics Cryocam

The data storage demands increase dramatically depending on the spatial and grey-scale resolution: 512 x 512 8-bit image = 262 KB 1024 x 1024 8-bit = 1,049 KB 1024 x 1024 12-bit = 1,573 KB 2048 x 2048 16-bit = 8,389 KB

Grey Level Resolution: The number of possible pixel values increases dramatically with relatively modest demands on data storage. 8-bit image 256 shades of grey 12-bit image 4096 shades of grey 16-bit image 65,536 shades of grey

If humans can only see ~100 shades of grey why bother with so much data? 8-bit 12-bit 16-bit

Bit-depth can be an important aspect of color images Bit-depth can be an important aspect of color images. The human eye can discern many different colors and hues so the “dynamic range” of a color image is important.