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In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more.This is accomplished by doing a convolution between the kernel and an image.
In general, defocus reduces the sharpness and contrast of the image. What should be sharp, high-contrast edges in a scene become gradual transitions. Fine detail in the scene is blurred or even becomes invisible. Nearly all image-forming optical devices incorporate some form of focus adjustment to minimize defocus and maximize image quality.
Transparency: render portions of an image invisible. Draw: add shapes or text to an image. Decorate: add a border or frame to an image. Special effects: blur, sharpen, threshold, or tint an image. Animation: assemble a GIF animation file from a sequence of images. Text and comments: insert descriptive or artistic text in an image.
For image processing, deconvolution is the process of approximately inverting the process that caused an image to be blurred. Specifically, unsharp masking is a simple linear image operation—a convolution by a kernel that is the Dirac delta minus a gaussian blur kernel.
If the new version is too sharp, you can utilize the blur filter or tool to fix this, or use Colors > Levels to mess with the Alpha channel. Once it looks correct, save the image as a PNG. Then, to reduce file size, run it through a program like ImageMagick that supports 8-bit PNGs with alpha transparency, in order to remove any unnecessary colors.
The blur makes the image less sharp, but prevents the formation of moiré pattern aliasing artifacts. Gaussian blurring is commonly used when reducing the size of an image. When downsampling an image, it is common to apply a low-pass filter to the image prior to resampling.