This Electronics Engineering Seminar Topic deals with the following:

An image defined in the “real world” is considered to be a function of two real variables say x,y.

Before going to processing an image, it is converted into a digital form. Digitization includes sampling of image and quantization of sampled values.

After converting the image into bit information, processing is performed.

This processing technique may be,

• Image enhancement
• Image reconstruction
• Image compression

Image enhancement refers to accentuation, or sharpening, of image features such as boundaries.

Image restoration is concerned with filtering the observed image to minimize the effect of degradations.

Image compression is concerned with minimizing the no of bits required to represent an image.

Text compression – CCITT GROUP3 & GROUP4

Still image compression – JPEG

Video image compression -MPEG

Modern digital technology has made it possible to manipulate multi-dimensional signals with systems that range from simple digital circuits to advanced parallel computers. The goal of this manipulation can be divided into three categories:        * Image Processing image in -> image out        * Image Analysis image in -> measurements out        * Image Understanding image in -> high-level description out Image processing is referred to processing of a 2D picture by a computer. Basic definitions:

An image defined in the “real world” is considered to be a function of two real variables, for example, a(x,y) with a as the amplitude (e.g. brightness) of the image at the real coordinate position (x,y).

An image may be considered to contain sub-images sometimes referred to as regions-of-interest, ROIs, or simply regions. This concept reflects the fact that images frequently contain collections of objects each of which can be the basis for a region. In a sophisticated image processing system it should be possible to apply specific image processing operations to selected regions. Thus one part of an image (region) might be processed to suppress motion blur while another part might be processed to improve color rendition. Sequence of image processing:

The most requirements for image processing of images is that the images be available in digitized form, that is, arrays of finite length binary words. For digitization, the given Image is sampled on a discrete grid and each sample or pixel is quantized using a finite number of bits. The digitized image is processed by a computer. To display a digital image, it is first converted into analog signal, which is scanned onto a display.

Sampling theorem:
A band limited image is sampled uniformly on a rectangular grid with spacing d x, d y can be recovered without error from the sample values f (mdx,ndy) provided the sampling rate is greater than nyquist rate, that is

The step subsequent to sampling in image digitization is quantization. A quantizer maps a continuous variable u into a discrete variable u1, which takes values from a finite set {r1, r2… rn} of numbers. This mapping is generally a staircase function & quantization rule is as follows:

Define {tk, k=1,…,L+1} as a set of increasing transition or decision levels with t1 and tL+1 as minimum and maximum values,respectively,of u. if u lies in intervals [tk,tL+1], then it is mapped to rk, the kth reconstruction level.           The following quantizers are useful in image coding techniques such as pulse code modulation (PCM), differential PCM, transform coding, etc., they are operate on one input sample at  a time, output value  depends only on that input. they are,
i.LLOYD-MAX QUANTIZER
ii.OPTIMUM MEAN SQUARE UNIFORM QUANTIZER

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