Image Compression Using DPCM Quantization

Abstract: Image processing modifies pictures to improve, extract information, and change their structure (composition, image editing, image compression, etc.). Images can be processed by optical, photographic, and electronic means, but image processing using digital computers is the most common method due to its speed, flexibility, and precision. Compression involves reducing redundancy in the image data to optimize transmission and storage. Differential Pulse Code Modulation (DPCM) is a method that uses prediction and quantization techniques to efficiently compress images by removing unused bits. In this paper, we evaluate the results of image compression using 3-bit DPCM quantization, analysing the in this study quality through histograms, prediction mean square error, and distortion levels. The results demonstrate that DPCM with 3-bit quantization achieves a good balance between image reconstruction and file size reduction, providing a clear trade-off between compression ratio and image quality. This paper explores the effects of 3- bit quantization on image compression, focusing on prediction accuracy and distortion.

Keywords: Image Compression, Quantization, Prediction Error, Image Processing.