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A co-occurrence matrix or co-occurrence distribution (also referred to as : gray-level co-occurrence matrices GLCMs) is a matrix that is defined over an image to be the distribution of co-occurring pixel values (grayscale values, or colors) at a given offset. It is used as an approach to texture analysis with various applications especially in ...
This article provides introductory information about the RGB, HSV, and HSL color models from a computer graphics (web pages, images) perspective. An introduction to colors is also provided to support the main discussion.
In data analysis applications, such as image processing, a lookup table (LUT) can be used to transform the input data into a more desirable output format. For example, a grayscale picture of the planet Saturn could be transformed into a color image to emphasize the differences in its rings.
For example, if applied to 8-bit image displayed with 8-bit gray-scale palette it will further reduce color depth (number of unique shades of gray) of the image. Histogram equalization will work the best when applied to images with much higher color depth than palette size, like continuous data or 16-bit gray-scale images.
Erosion (usually represented by ⊖) is one of two fundamental operations (the other being dilation) in morphological image processing from which all other morphological operations are based. It was originally defined for binary images, later being extended to grayscale images, and subsequently to complete lattices.
For each unique palette, an image color test chart and sample image (truecolor original follows) rendered with that palette (without dithering) are given. The test chart shows the full 8-bit, 256 levels of the red, green, and blue primary colors and cyan, magenta, and yellow complementary colors, along with a full 8-bit, 256 levels grayscale.
Quantitative schemes are fundamental to Thematic maps, charts, data science, spreadsheets, and other tools which use graphical means to visualize quantitative data. They are common in heat maps, choropleths and other forms of visualization. These color schemes can be categorized into different classes, depending on the nature of the underlying ...
The supported colors could be stippled in 2×2 blocks to simulate up to 256 colors, an effect which did not copy reliably on a TV, especially over an RF connection. Pixel aspect ratio was not square, with resulting image proportions close to 4.4:3, making the image extend into the horizontal overscan area of a CRT TV.