给出 image 与内核 ker 的卷积.
- ImageConvolve performs the convolution operation on an image. Convolution is an integral (or its discrete analog) that expresses the amount of overlap of one function as it is shifted over another. Convolution therefore “blends” one function or image with another and can be used to perform many useful operations on images such as smoothing, feature extraction, and differentiation.
- The “smoothing” function that is shifted over an image to perform convolution is a matrix known as a kernel, and many different kinds of kernels are possible and useful depending on context. GaussianFilter and MeanFilter are special cases of ImageConvolve that use a Gaussian and the mean value in a given range, respectively, as their kernels.
- ImageConvolve is a local operation, meaning it produces output pixel values based only upon the pixel values in its neighborhood as determined by the kernel. It is also a linear one, meaning it is convolution-based and replaces each pixel by a linear combination of its neighbors.
- The converse operation to ImageConvolve is ImageDeconvolve. The function ListConvolve performs the operation of convolution on lists (as opposed to images).