The mathematical process by which raw data undergo spatial filtration prior to back projection.
Spatial filtering based on a weighted sum of neighboring pixels.
An image-processing operation frequently used to sharpen an image, blur an image, or highlight the edges in an image. The operation calculates the values of pixels in the destination image using the values of a neighborhood of pixels in the source image and the values in a special filter called a convolution kernel.
An image processing operation calculates for each source pixel a weighted average of the pixels in the neighborhood of the source pixel. The weights are stored in a kernel or convolution mask. Used to implement a common class of image processing filters, like high and low pass, and edge enhancement.
A common image-processing operation that can be used to filter an image. The filtering is accomplished by computing the sum of products between the source image and a smaller image or matrix called the convolution filter or convolution kernel. The convolution filter can be loaded with different values to achieve effects like sharpening, blurring, and edge detection.
a mathematical function that replaces each pixel by a weighted sum of its neighbors
a mathematical method whereby a pixel's gray value is determined by the pixels surrounding it
a spatial operation where the pixels surrounding the input pixel are multiplied by a kernel value to generate the value of the output pixel
An image processing filter that considers a region of pixels in the source image when calculating the resulting value for a single pixel in the destination image
An identical operation to Finite Impulse Response filtering.
A mathematical operation to weight the value of a pixel by those of pixels which surround it.
A mathematical operation between two functions. [ Chapter 2
Superimposing an m x n operator (usually a 3x3 or 5x5 mask) over an area of the image, multiplying the points together, summing the results to replace the original pixel with the new value. This operation can be performed on the entire image or regions of interests to enhance edges, features, remove noise and other filtering operations.