"基于MATLAB的JPEG基本系统编码及优势分析"

Based on the document "JPEG Basic System Encoding Based on MATLAB", this paper introduces the basic system encoding of JPEG based on MATLAB. In the process of image transmission, JPEG format is often used to compress and encode static images. The JPEG basic system encoding first divides the grayscale image into 8×8 pixel blocks, and then performs discrete cosine transform on each pixel block to obtain the transformation coefficients, and then performs quantization. Next, the quantized transformation coefficients are scanned in a zigzag pattern to obtain DC coefficients and AC coefficients. Then, predictive coding is applied to the DC coefficients, and variable-length coding is applied to the AC coefficients. Finally, Huffman coding is used to perform entropy coding according to the standard, outputting the bit sequence of the compressed image, thereby achieving image compression. At the receiving end, after Huffman decoding, variable-length decoding of DC coefficients and AC coefficients, and inverse quantization, the image is reconstructed by performing inverse discrete cosine transform. MATLAB simulation results show that the reconstructed image has almost no difference from the original image and can meet people's visual needs. In addition, the data compression ratio is about 10 times, and the peak signal-to-noise ratio is above 30dB. Therefore, using MATLAB to implement the JPEG basic system encoding has advantages such as simple method, fast speed, and small errors, which can greatly improve the efficiency and accuracy of image compression. Keywords: JPEG, discrete cosine transform, MATLAB, graphical user interface.