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Matplotlib-animation [11] capabilities are intended for visualizing how certain data changes. However, one can use the functionality in any way required. These animations are defined as a function of frame number (or time). In other words, one defines a function that takes a frame number as input and defines/updates the matplotlib-figure based ...
Corel Image Features Data Set Database of images with features extracted. Many features including color histogram, co-occurrence texture, and colormoments, 68,040 Text Classification, object detection 1999 [189] [190] M. Ortega-Bindenberger et al. Online Video Characteristics and Transcoding Time Dataset.
Image data that uses indexed color specifies addresses within the CLUT to provide the required R, G, and B values for each specific pixel, one pixel at a time. Of course, before displaying, the CLUT has to be loaded with R, G, and B values that define the palette of colors required for each image to be rendered.
The image modification process is sometimes called color transfer or, when grayscale images are involved, brightness transfer function (BTF); it may also be called photometric camera calibration or radiometric camera calibration. The term image color transfer is a bit of a misnomer since most common algorithms transfer both color and shading ...
The resulting image is larger than the original, and preserves all the original detail, but has (possibly undesirable) jaggedness. The diagonal lines of the "W", for example, now show the "stairway" shape characteristic of nearest-neighbor interpolation. Other scaling methods below are better at preserving smooth contours in the image.
A 2-bit indexed color image. The color of each pixel is represented by a number; each number (the index) corresponds to a color in the color table (the palette).. In computing, indexed color is a technique to manage digital images' colors in a limited fashion, in order to save computer memory and file storage, while speeding up display refresh and file transfers.
CIFAR-10 is a set of images that can be used to teach a computer how to recognize objects. Since the images in CIFAR-10 are low-resolution (32x32), this dataset can allow researchers to quickly try different algorithms to see what works. CIFAR-10 is a labeled subset of the 80 Million Tiny Images dataset from 2008, published in 2009. When the ...
This creates a so called 3-3-2 8-bit color image, arranged like on the following table: Bit 7 6 5 4 3 2 1 0 Data R R R G G G B B. This process is sub optimal. There could be different groupings of colors that make evenly spreading the colors out inefficient and likely to misrepresent the actual image.