Wavelet Transform Image Enhancement with Nonlinear Processing

In this content, we can incorporate additional details to expand the text. We can describe the specific steps and principles of the wavelet transform image enhancement program, including multi-scale decomposition using functions like wavedec2 for 2D signals, coefficient modification through hard/soft thresholding techniques, and image reconstruction using waverec2. The nonlinear processing component involves algorithms such as histogram equalization (histeq function) or contrast-limited adaptive histogram equalization (adapthisteq) for local enhancement. We can also elaborate on the working principles and application scope of nonlinear processing methods, including gamma correction and sigmoid filtering for dynamic range adjustment. Furthermore, we can mention the usage methods in the MATLAB compilation environment, detailing key functions such as wdencmp for denoising applications, wavedec for decomposition levels selection, and wavelet family selection (e.g., 'db4', 'sym8'). By adding these technical implementation details, we can make the text more comprehensive and suitable for computational image processing applications.