Abstract:-Wavelet-based image compression has been the subject of recent study. We suggest a compression method based on modifying the original EZW coding in it. We strive to eliminate less significant information in the image data in this lossy technique in order to achieve additional compression with little impact on output image quality. In each level, the algorithm calculates the weight of each sub-band and determines the sub-band with the least weight. Each level's smallest weight sub-band, which has the least effect during image reconstruction, passes through a threshold process to remove low-valued data. During the experiment, several threshold settings were used to determine how they affected the compression ratio and reconstructed image quality. As a result of the proposed strategy, the compression ratio is increased even more.
The rapid advancement of computing technologies has resulted in a demand for digital photographs. The expense of manipulating, storing, and transmitting these photos in their raw form is prohibitively expensive, slowing transmission and increasing storage costs. A quick review of wavelet transform theory is given in this study, with filters used as examples to demonstrate multiresolution analysis. The advantages of the Fourier transform are studied, and numerous conclusions are drawn. The pyramid algorithm is also discussed, as well as several wavelet aspects in image data compression. image quality isn't harmed in the process.
Keywords:-Image compression, Wavelet image Compression, Embedded Zero coding, Sub band Coding.
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DOI:
10.17148/IJARCCE.2022.11311
