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2. Gaussian blur - Wikipedia

   en.wikipedia.org/wiki/Gaussian_blur

   The difference between a small and large Gaussian blur. In image processing, a Gaussian blur (also known as Gaussian smoothing) is the result of blurring an image by a Gaussian function (named after mathematician and scientist Carl Friedrich Gauss). It is a widely used effect in graphics software, typically to reduce image noise and

3. Bokeh - Wikipedia

   en.wikipedia.org/wiki/Bokeh

   From left to right: an original photo with no bokeh or blur; the same photo with synthetic bokeh effect applied to its background; the same photo with Gaussian blur applied to its background. Bokeh can be simulated by convolving the image with a kernel that corresponds to the image of an out-of-focus point source taken with a real camera.

4. Miniature faking - Wikipedia

   en.wikipedia.org/wiki/Miniature_faking

   Miniature faking, also known as diorama effect or diorama illusion, is a process in which a photograph of a life-size location or object is made to look like a photograph of a miniature scale model.

5. Unsharp masking - Wikipedia

   en.wikipedia.org/wiki/Unsharp_masking

   The software applies a Gaussian blur to a copy of the original image and then compares it to the original. If the difference is greater than a user-specified threshold setting, the images are (in effect) subtracted. Digital unsharp masking is a flexible and powerful way to increase sharpness, especially in scanned images.

6. Neutral-density filter - Wikipedia

   en.wikipedia.org/wiki/Neutral-density_filter

   A demonstration of the effect of a neutral density filter. Note that the photograph was exposed for the view through the filter, and thus the remainder of the scene is overexposed. If the exposure had instead been set for the unfiltered background, it would appear properly exposed while the view through the filter would be dark. A set of ND filters

7. Kernel (image processing) - Wikipedia

   en.wikipedia.org/wiki/Kernel_(image_processing)

   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.