Advanced Image Detection and Processing Using MATLAB

A Whole Picture of Image Process for Image Detection and Processing by MATLAB which is Joint with Contrast Enhancement, Noise Reduction, Edge Detection and Segmentation. This paper introduced a methodology used in image detection and processing by MATLAB, which includes contrast enhancement, noise reduction, edge detection and segmentation. A properly tuned pipeline of CLAHE (Contrast Limited Adaptive Histogram Equalization), Canny edge detection, and thresholding according to Otsu’s method, is suggested and tested using both PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index). Both quantitative and qualitative results show that our approach outperforms the previous state-of-the-art methods, especially in medical and industrial imaging. Challenges in the low light conditions are described, and future avenues are proposed.