An Efficient Image Compression Method by Using Optimized Discrete Wavelet Transform and Huffman Encoder

摘要

Image compression performs a vital role for image transmission and storage. Image compression signifies diminishing the image size, with no loss in the image quality. For mitigating the storage necessities of image transmission, image compression approach is projected to proffer a compact illustration of an image. Even though the image compression methodology has a salient role for compressing images certain conflicts are still present in these techniques. We introduced a unique image compression methodology by pooling Single Value Decomposition (SVD) and optimized Discrete Wavelet Transform (DWT). In the initial stage, the input image is subjected to decomposition through SVD. The decomposed image thus obtained is restored through inverse SVD. The restored image thus achieved is inputted to the DWT, where the optimization is performed through a renowned optimization technique called genetic algorithm (GA). Consequently the processing speed gets increased. The outcome of the optimized DWT process will be given as input to the Huffman encoding and decoding. Finally, the actual image is regained through Inverse Discrete Wavelet Transform (IDWT) process, for attaining the decompressed image. Our suggested technique of image compression will be applied in MATLAB platform. The operation of our image decomposition methodology will be analyzed by a lot of other images. Moreover the performance will be compared with the prevailing techniques according to Peak Signal Noise Ratio (PSNR), Structural Similarity Index Measurement (SSIM), Mean Square Error (MSE), and Compression Ratio (CR).