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The same differencing principle is used in the unsharp-masking tool in many digital-imaging software packages, such as Adobe Photoshop and GIMP. [1] 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 ...
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 reduce detail.
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.
A box blur (also known as a box linear filter) is a spatial domain linear filter in which each pixel in the resulting image has a value equal to the average value of its neighboring pixels in the input image. It is a form of low-pass ("blurring") filter.
With basic techniques, e.g., a tool such as Adobe Photoshop's Lens Blur filter, [9] using sharpness gradients extending from the middle of the image to the top and bottom, the effect is quite similar to that obtained using lens tilt. The simple techniques have limitations similar to those of lens tilt.
The most common is a soft edge and provides a smooth transition from the ND side and the clear side. Hard-edge filters have a sharp transition from ND to clear, and the attenuator edge changes gradually over most of the filter, so the transition is less noticeable. Another type of ND filter configuration is the ND-filter wheel. It consists of ...
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