Single-Stage Image Compression Based on Wavelet Transform

This program implements an image compression method based on wavelet transform, which effectively reduces image data volume to save storage space and transmission time. The algorithm works by decomposing the image into frequency subbands at different scales through wavelet transformation, then applying quantization processing to each subband. This process removes redundant information from the image while preserving essential image features. In code implementation, key functions typically include wavelet decomposition (using filters like Daubechies or Haar), threshold-based coefficient quantization, and entropy encoding. This image compression method is widely used in digital image processing and communication fields, significantly improving image transmission efficiency and storage performance. The implementation typically involves calculating wavelet coefficients, applying thresholding to eliminate insignificant coefficients, and reconstructing the image from the compressed coefficients.