Combining of Spatial and Frequency Domain Transformation With The Effect of Using and Non-Using Adaptive Quantization for Image Compression
Usage of image has been increasing and used in many applications. Image compression plays vital role in saving storage space and saving time while sending images over network. One important point of delivering digital image is time. In this paper we concentrated on the speed of packet sending with reasonable quality. The aim of this paper is to reduce image size with reasonable quality. By getting advantage from image transformation in both scope spatial domain and frequency domain. Splitting the image into 4 blocks in the case of spatial domain and applying Standard Haar wavelet transformation in the case of frequency domain was the main factor for approaching the aim of this paper which was reduce image size and increase speed of delivering digital image. After huge tests in the case of frequency domain in all subbands(LL,HL,LH,HH) we made a decision for which subband contains high information and which subband contains poor information. Depending of these factors we could send less than one- eighth of the size of the original image to the destination and getting the reconstructed image with the acceptable quality as a result of this paper.
Keywords: Haar Wavelet Transformation, Adaptive Quantization, Spatial Domain, Frequency Domain, PSNR, Mean Square Error, Compression Ratio, Variable Encoding RLE, Image Quality
Download Full-Text
