Chapter 13: MATLAB Image Enhancement Techniques

This chapter explores various MATLAB image enhancement methods. Section 13.1 covers gray-scale transformation enhancement, including pixel values and their statistical properties, with detailed explanations of histogram gray-scale transformation, histogram equalization, and histogram specification techniques. Implementation typically involves MATLAB's histeq() function for equalization and custom mapping functions for specification. Section 13.2 discusses spatial filtering enhancement, focusing on applications of smoothing filters (using fspecial() with 'average' or 'gaussian' options) and sharpening filters (employing Laplacian or unsharp masking techniques through imfilter()). Section 13.3 introduces frequency domain enhancement, covering low-pass filters (ideal/Butterworth/Gaussian implementations via fft2()), high-pass filters, homomorphic filters for illumination correction, and practical MATLAB examples demonstrating frequency domain operations. Section 13.4 examines color enhancement techniques, including true color enhancement (channel-wise processing using rgb2hsv() and color balance adjustments) and pseudo-color enhancement (gray-scale to color mapping with colormap manipulation). Finally, Section 13.5 presents wavelet enhancement concepts, explaining multi-resolution analysis through wavelet decomposition/reconstruction using wavedec2() and waverec2() functions for noise reduction and detail enhancement applications. All sections include MATLAB code examples to facilitate practical understanding.