Image Compression Using High Level Wavelet Transformer with Non-Uniform Quantizer and Different Levels Huffman Codes

Abstract

Image compression solutions are a pivotal field that gain over a remarkable research interest and called upon to extend widely with respect to the increasing of its applications. The considerable challenge of this solution is related to the storage and bandwidth requirements. A highly compression rate with a high image resolution is considered to be the key factors for implementing a robust image compression technique. In this paper, the proposed method is deemed to be simple and effective due to using different levels of compression process which is starting from dividing the image into sub-images and using high level discrete wavelet transform (DWT). In addition, the Huffman code with non-uniform Quantizer has been used to minimize the compression data rate with high quality reconstructed image. The promising simulation results of the proposed method achieved the most two significant criteria which are denoted by high image quality and a high image compressed ratio. For instance, the proposed strategy simulation results of Lena image achieved PSNR equals to 42.4094 dB with a compression ratio (CR) equals to 47.5435. Moreover, the simulation results of Flower image accomplished PSNR equals to 42.8348 dB with a compression ratio equals to 55.3389 under the same simulation conditions.