Explore MATLAB source code curated for "压缩" with clean implementations, documentation, and examples.
Compress a raw video image sequence to generate a compressed file; decompress this compressed file to produce a display image; compare the display image with the original image in terms of quality, compressed file size, and other relevant metrics.
Chapter on Image Coding and Compression: Fundamentals of Image Coding, Lossless Compression Coding including Run-Length Encoding, Huffman Coding, Arithmetic Coding, Dictionary Coding; Lossy Compression Coding covering Predictive Coding, Orthogonal Transform Coding; MATLAB Implementation of Cosine Transform Compression and Wavelet Transform Compression (Section 17.3.4)
The Retinex algorithm enables adaptive enhancement for various image types, offering superior adaptability compared to traditional single-method enhancement approaches. While conventional algorithms typically enhance only specific image features, Retinex achieves optimal balance in dynamic range compression, detail enhancement, and color correction through its multi-scale processing approach using Gaussian surround functions. Primarily applied in underwater image restoration, the algorithm's core implementation involves separating illumination and reflectance components through logarithmic operations and spatial filtering.
Achieve grayscale image compression and decoding using run-length encoding and Huffman coding, achieving compression ratios up to 15:1 through efficient data representation and entropy coding techniques.
Spatial coherence often exists between color values of sampling points across an image surface - for instance, the identical coloration of two mice, the background wall, and gray floor. These uniform color blocks can be effectively compressed through algorithms like run-length encoding or discrete cosine transform.
This implementation demonstrates wavelet decomposition and reconstruction for image denoising and compression, featuring flexible wavelet selection and beginner-friendly code structure with detailed comments explaining key functions like wavedec2 and waverec2.
Implementation of JPEG image compression and encoding using MATLAB programming, including DCT transformation, quantization, and Huffman coding algorithms.
Implementation of SAR echo simulation for stationary targets using Range Doppler Algorithm (RDA) for data compression and imaging, including signal processing workflow and MATLAB/Python code structure
MATLAB implementation of Singular Value Decomposition (SVD) algorithm for compressing bitmap images in .bmp format, including detailed code explanation and compression methodology
An approach to image sparse coding applicable for sparse representation-based image compression, denoising, and related tasks