Image Enhancement Preview The principal objective of enhancement

Image Enhancement Preview The principal objective of enhancement is to process an image so that the result is more suitable than the original image for a specific application. The word specific is important, because it establishes at the outset that the techniques discussed in this chapter are very much problem oriented. Thus, for example, a method that is quite useful for enhancing Xray images may not necessarily be the best approach for enhancing pictures of Mars transmitted by a space probe. Regardless of the method used, however, image enhancement is one of the most interesting and visually appealing areas of image processing. Image enhancement approaches fall into two broad categories : spatial domain methods and frequency domain methods. The term spatial domain refers to the image plane itself, and approaches in this category are based on direct manipulation of pixels in an image.

Background Spatial domain processes

Threshold

Some Basic Gray Level Transformations • 1. 2. Linear: identity negative Logarithmic: log inverse-log Power-law: nth power nth root

Inverse or

Inverse Example Intensity. Max=23 r=the value of (x, y) (pixels of orginal image) • • New Pixel 1=23 -23=0 New Pixel 2=23 -16=7 New Pixel 3=23 -6=17 New Pixel 4=23 -9=14 Original Image New Image 23 16 Pixel 1 Pixel 2 0 7 6 9 Pixel 3 Pixel 4 17 14

Log Transformations

Power-Law Transformations

Gamma Correction

Gamma Correction

Power-Law Transformations

Contrast stretching

Gray-level slicing

Bit-plane slicing

Enhancement Using Arithmetic/Logic Operations Pixel-by-pixel between 2 or more images (NOT: 1 image) 1. Logic operations: AND, OR, NOT • Operate on strings of binary numbers • NOT: performs negative transformation • AND, OR: masking, region of interest (ROI) processing 2. Arithmetic operations: −, +, ×, / • −, +: more important

Logic operations

Arithmetic Operations Image Subtraction

Image Adding

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