Image Compression Technology Based on Wavelet Transform

Abstract

Image compression based on wavelet transform is to apply wavelet algorithm to multi-resolution decomposition of the image, and to achieve image compression by encoding the obtained wavelet coefficients. First, multi-level wavelet decomposition is performed on the image to obtain the corresponding wavelet coefficients. Then, each layer of wavelet coefficients is quantized to obtain quantized coefficient objects. Finally, the quantized coefficient objects are encoded to obtain compression results. This paper uses Haar wavelet as the wavelet base, selects the 2-level decomposition scale, performs wavelet transform, compresses the reconstructed image by setting a threshold, and calculates the file size ratio and PSNR value before and after compression. The wavelet reconstruction function uses the coefficient matrix, dimensionality information and wavelet base type obtained by wavelet decomposition to perform wavelet reconstruction. The global threshold setting method is selected, and the wavelet high-frequency coefficients are threshold filtered to achieve compression before the reconstruction operation, and then the compressed image is obtained through wavelet reconstruction. After the image has undergone wavelet transformation with a specified scale, most of the energy is concentrated in the fractional part of the wavelet decomposition coefficients. The coefficients of other parts are set to constants by setting a threshold, and only a few decomposition coefficients are retained to represent the entire image.The experimental results show that the storage space of the compressed image is greatly saved and the compressed image does not change significantly from the original image visually.