Huffman Coding for Image Compression and Decompression

Huffman coding is an excellent algorithm for image compression and decompression, widely applicable to various types of image processing. The algorithm achieves efficient compression by mapping frequently occurring pixel values to shorter codes while assigning longer codes to less common pixel values, effectively reducing overall data size. Key implementation steps include: 1. Calculating pixel value frequencies from the image histogram 2. Constructing a Huffman tree using a priority queue (min-heap) 3. Generating variable-length codes through tree traversal 4. Encoding image data by replacing pixels with corresponding Huffman codes Using Huffman coding significantly reduces image file sizes, conserves storage space, and enhances transmission speed. The decompression process involves reconstructing the Huffman tree from stored frequency data and decoding the bitstream back to original pixel values. Thus, Huffman coding serves as a highly practical technique in image processing workflows, particularly beneficial for lossless compression scenarios.