Comparative Analysis for Dct, Dwt Image Compression Performed with Huffman, Run Length and Lzw Encoding
Keywords:
Image Compression, DCT, DWT, HE, RLE, LZW, PSNR, CR, SSIM, MSEAbstract
An enormous amount of storage space is required for uncompressed digital photographs. Using image compression, the amount of storage space needed to store and transmit images and videos can be reduced. We focus on image compression not just in terms of reducing file size, but also in keeping image quality and information. Two different methods of compressing images are examined in this research article. DCT (Discrete Cosine Transform) and DWT (Discrete Wavelet Transform) with Huffman Encoding, Run-length Encoding, and LZW Encoding (DWT). Peak Signal Noise Ration (PSNR), Compression Ratio (CR), Mean Square Error (MSE), Structural Similarity Index measure (SSIM) and compression/decompression time are all used to evaluate the performance of these tools. Many images are subjected to a variety of quality controls before the simulation results are displayed and compared to the originals.