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wavelift
- 暂时只支持jpeg2000支持的 cdf97 和spline53 可以这样来测试： x=imread( E:\\study\\jpeg2000\\images\\lena.tif ) ％ see the decomposition coefficients y=wavelift(x, 1, spl53 ) using spline 5/3 wavelet figure subplot(1,2,1) imshow(x) subplot(1,2,2) imshow(mat2g
234
- 本设计是针对第二题采用了两种算法用来识别各种水果。第一种算法是质心法，第二种方法是相关匹配法。 质心法 一．算法思想 质心法的优点在于图像经过任何旋转后，图像边缘到质心的距离求和始终为一个固定值，这样利用这一个特性，就可以辨识出各个图像。 -This design is the second title for the two algorithms used to identify a variety of fruits. The first is a qualitative-f
DiscreteCosineTransform
- DCT A discrete cosine transform (DCT) expresses a sequence of finitely many data points in terms of a sum of cosine functions oscillating at different frequencies. DCTs are important to numerous applications in science and engineering, from lossy com
SDD
- Function-Compute Correlation between two images using the similarity measure of Sum of Squared Differences (SSD) with Right Image
dct
- A discrete cosine transform (DCT) expresses a finite sequence of data points in terms of a sum of cosine functions oscillating at different frequencies. DCTs are important to numerous applications in science and engineering, lossy compression of audi
data_batch_2
- cifar-10数据集由10个类的60000个32x32彩色图像组成，每个类有6000个图像。有50000个训练图像和10000个测试图像。数据集分为五个训练批次和一个测试批次，每个批次有10000个图像。测试批次包含来自每个类别的恰好1000个随机选择的图像。训练批次以随机顺序包含剩余图像，但一些训练批次可能包含来自一个类别的图像比另一个更多。总体来说，五个训练集之和包含来自每个类的正好5000张图像。 具体：batch2.mat文件，该训练集可以用于图片识别，非负矩阵分解等。(The ci