MATLAB Implementation of JPEG Encoding and Decoding with Full Process Details

This article provides detailed MATLAB implementations of the complete JPEG encoding and decoding pipeline, featuring comprehensive functions and procedures for image format conversion, zero-bias transformation, Discrete Cosine Transform (DCT), quantization, AC coefficient encoding with run-length coding, zigzag scanning pattern implementation, DC coefficient differential encoding, JPEG decoding algorithms, inverse DCT transformation, and image reconstruction processes. The implementation includes MATLAB code for handling 8x8 block processing, where each block undergoes forward DCT transformation using dct2() function, followed by quantization using standard JPEG quantization tables. The zigzag scanning is implemented through predefined index mapping to convert 2D coefficient matrices into 1D sequences. Additionally, the content can be extended to include fundamental image processing principles and techniques such as color space conversion (RGB to YCbCr), filter applications for noise reduction, edge detection algorithms, and compression optimization methods. Practical examples and case studies can be incorporated to help readers better understand and apply the acquired knowledge through hands-on MATLAB coding exercises. By providing detailed explanations of the encoding/decoding workflow and expanding on related image processing concepts, this resource enables readers to develop a comprehensive and in-depth understanding of JPEG compression techniques and their MATLAB implementation, including performance optimization considerations and error analysis in reconstruction quality.