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Image compression is a type of data compression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data.
Composite image showing JPG and PNG image compression. Left side of the image is from a low-quality JPEG image, showing lossy artefacts; the right side is from a PNG image.
Take a 4×4 block from an image, in this case the mountain test image: [7] Like any small block from an image this appears rather boring to work with as the numbers are all quite similar, this is the nature of lossy compression and how it can work so well for images.
Three types of pictures (or frames) are used in video compression: I, P, and B frames.. An I‑frame (intra-coded picture) is a complete image, like a JPG or BMP image file.. A P‑frame (Predicted picture) holds only the changes in the image from a previous frame.
Image quality can be assessed using objective or subjective methods. In the objective method, image quality assessments are performed by different algorithms that analyze the distortions and degradations introduced in an image.
The term resolution is often considered equivalent to pixel count in digital imaging, though international standards in the digital camera field specify it should instead be called "Number of Total Pixels" in relation to image sensors, and as "Number of Recorded Pixels" for what is fully captured.
The ImageNet project is a large visual database designed for use in visual object recognition software research. More than 14 million [1] [2] images have been hand-annotated by the project to indicate what objects are pictured and in at least one million of the images, bounding boxes are also provided. [3]
Brotli's new file format allows its authors to improve upon Deflate by several algorithmic and format-level improvements: the use of context models for literals and copy distances, describing copy distances through past distances, use of move-to-front queue in entropy code selection, joint-entropy coding of literal and copy lengths, the use of graph algorithms in block splitting, and a larger ...