Image Compression: Algorithms, Techniques and Applications

R. S. Bature, U. B. Agballa, K. Umar, U. E. Okon

Abstract


In the digital age, the proliferation of images necessitates efficient storage and rapid transmission methods to manage the vast amounts of data generated. This paper explores the critical role of image compression, which serves to reduce file sizes while maintaining acceptable quality levels. It distinguishes between two primary types of compression: lossless, which preserves original data integrity, and lossy, which sacrifices some detail for greater size reduction. The reviews of various image compression algorithms, including JPEG and PNG, and highlights advanced techniques such as wavelet transforms and deep learning methodologies that have emerged to address the challenges posed by high-resolution images were also carried out. By examining the strengths and weaknesses of these methods, this paper underscores the importance of ongoing research in image compression to enhance storage efficiency and transmission speed, ultimately contributing to improved user experiences in digital media.


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References


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