A REVIEW ON IMAGE COMPRESSION
DOI:
https://doi.org/10.65009/xneh2e87Keywords:
Image Compression, Arithmetic Coding, Run Length Encoding, MSE, PSNR,,Abstract
Storage, connection, and quicker computation are the three most important components that
the world of image processing requires at the moment. In order to facilitate the transfer of these three
features to programs that deal with image processing, picture compression is utilized. There is a large
variety of algorithms and methods that can be utilized for both lossless and lossy image compression.
This piece of work provides a comprehensive literature review of image compression techniques, which
includes an analysis of the underlying principles and approaches that are available, as well as the
requirements for further research. A model is proposed for the purpose of reinforcing ROI-based
compression approaches. This model is based on the dissociation of ROI and Non-ROI sections of the
image. Huffman Encoding is used to compress ROI, and Quad Tree Decomposition is used to compress
non-ROI components. Compression Ratio (CR), Mean Square Error (MSE), Peak Signal to Noise Ratio
(PSNR), and Bits Per Pixel are the evaluation metrics that are utilized in order to assess the effectiveness
of the image compression approaches that have been explored (BPP). According to the results of the
performance evaluation, the technique that was suggested functions better than other possible techniques.
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