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boundstoobox for evalution denoised image. This toolkit contains the main Matlab function and other required functions to estimate the bound on the MSE that can be expected in denoising a given image.
Update : 2025-02-19 Size : 1.51mb Publisher : z

计算均方误差MSE信噪比SNR峰值信噪比PSNR绝对平均误差的matlab函数-Calculate the mean square error MSE, SNR is the peak signal to noise ratio PSNR absolute average error of Matlab functions
Update : 2025-02-19 Size : 4kb Publisher : 新雨

DL : 0
均方误差信噪比 峰值信噪平均绝对误差的计算-Write MATLAB functions that take two grayscale images as input, and calculate the following image difference metrics:  Mean Squared Error (MSE)  Signal to Noise Ratio(SNR)  Peak Signal to Noise Ratio (PSNR)  Mean Absolute Error (MAE) Process the given test images “Lena” with its original and after-adding-noise
Update : 2025-02-19 Size : 3kb Publisher : 宁可

DL : 0
灰度图像的量化和直方图均衡化直接调用函数。量化是指将像素灰度转换成离散的整数值的过程。量化等级越多,所得图像层次越丰富,灰度分辨率高,图像质量好,但数据量大。-Write MATLAB functions to quantize grayscale image with given quantization step Q. Process the given test images “Lena” with quantization steps Q=2, 4, 8 16, 32, 64, 128. Calculate the MSE for the original and quantized images using MATLAB methods written for the Task 1. Plot the MSE for the test image as a function of quantization step Q. Show quantized images and the corresponding histograms for each quantization step Q. Show the test image and its histogram.
Update : 2025-02-19 Size : 3kb Publisher : 宁可
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