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Peak Signal-to-noise Ratio
Peak signal-to-noise ratio (PSNR) is an engineering term for the ratio between the maximum possible power of a signal and the power of corrupting noise that affects the fidelity of its representation. Because many signals have a very wide dynamic range, PSNR is usually expressed as a logarithmic quantity using the decibel scale. PSNR is commonly used to quantify reconstruction quality for images and video subject to lossy compression. Definition PSNR is most easily defined via the mean squared error (''MSE''). Given a noise-free ''m''×''n'' monochrome image ''I'' and its noisy approximation ''K'', ''MSE'' is defined as : \mathit = \frac\sum_^\sum_^ (i,j) - K(i,j)2. The PSNR (in dB) is defined as : \begin \mathit &= 10 \cdot \log_ \left( \frac \right) \\ &= 20 \cdot \log_ \left( \frac \right) \\ &= 20 \cdot \log_(\mathit_I) - 10 \cdot \log_ (\mathit). \end Here, ''MAXI'' is the maximum possible pixel value of the image. When the pixels are represented using 8 bits pe ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Signal (information Theory)
A signal is both the process and the result of Signal transmission, transmission of data over some transmission media, media accomplished by embedding some variation. Signals are important in multiple subject fields including signal processing, information theory and biology. In signal processing, a signal is a function that conveys information about a phenomenon. Any quantity that can vary over space or time can be used as a signal to share messages between observers. The ''IEEE Transactions on Signal Processing'' includes audio signal, audio, video, speech, image, sonar, and radar as examples of signals. A signal may also be defined as observable change in a quantity over space or time (a time series), even if it does not carry information. In nature, signals can be actions done by an organism to alert other organisms, ranging from the release of plant chemicals to warn nearby plants of a predator, to sounds or motions made by animals to alert other animals of food. Signa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Libjpeg
libjpeg is a free library with functions for handling the JPEG image data format. It implements a JPEG codec (encoding and decoding) alongside various utilities for handling JPEG data. It is written in C and distributed as free software together with its source code under the terms of a custom permissive (BSD-like) free software license, which demands attribution. The original variant is maintained and published by the Independent JPEG Group (IJG). Meanwhile, there are several forks with additional features. JPEG JFIF images are widely used on the Web. The amount of compression can be adjusted to achieve the desired trade-off between file size and visual quality. Utilities The following utility programs are shipped together with libjpeg: ; cjpeg and djpeg: for performing conversions between JPEG and some other popular image file formats. ; rdjpgcom and wrjpgcom: for inserting and extracting textual comments in JPEG files. ; jpegtran: for transformation of existing JPEG files. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Image Compression
Image compression is a type of data compression applied to digital images, to reduce their cost for computer data storage, storage or data transmission, 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. Lossy and lossless image compression Image compression may be lossy compression, lossy or lossless compression, lossless. Lossless compression is preferred for archival purposes and often for medical imaging, technical drawings, clip art, or comics. Lossy compression methods, especially when used at low bit rates, introduce compression artifacts. Lossy methods are especially suitable for natural images such as photographs in applications where minor (sometimes imperceptible) loss of fidelity is acceptable to achieve a substantial reduction in bit rate. Lossy compression that produces negligible differences ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Video Multimethod Assessment Fusion
Video Multimethod Assessment Fusion (VMAF) is an objective full-reference video quality metric developed by Netflix in cooperation with the University of Southern California, the IPI/LS2N lab Nantes Université, and the Laboratory for Image and Video Engineering (LIVE) at The University of Texas at Austin. It predicts subjective video quality based on a reference and distorted video sequence. The metric can be used to evaluate the quality of different video codecs, encoders, encoding settings, or transmission variants. History The metric is based on initial work from the group of Professor C.-C. Jay Kuo at the University of Southern California. Here, the applicability of fusion of different video quality metrics using support vector machines (SVM) has been investigated, leading to a "FVQA (Fusion-based Video Quality Assessment) Index" that has been shown to outperform existing image quality metrics on a subjective video quality database. The method has been further developed in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Subjective Video Quality
Subjective video quality is video quality as experienced by humans. It is concerned with how video is perceived by a viewer (also called "observer" or "subject") and designates their opinion on a particular video sequence. It is related to the field of Quality of Experience. Measuring subjective video quality is necessary because objective quality assessment algorithms such as PSNR have been shown to correlate poorly with subjective ratings. Subjective ratings may also be used as ground truth to develop new algorithms. Subjective video quality tests are psychophysical experiments in which a number of viewers rate a given set of stimuli. These tests are quite expensive in terms of time (preparation and running) and human resources and must therefore be carefully designed. In subjective video quality tests, typically, SRCs ("Sources", i.e. original video sequences) are treated with various conditions (HRCs for "Hypothetical Reference Circuits") to generate PVSs ("Processed Video ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Structural Similarity Index Measure
The structural similarity index measure (SSIM) is a method for predicting the perceived quality of digital television and cinematic pictures, as well as other kinds of digital images and videos. It is also used for measuring the similarity between two images. The SSIM index is a Video quality#Classification of objective video quality models, full reference metric; in other words, the measurement or prediction of image quality is based on an initial uncompressed or distortion-free image as reference. SSIM is a perception-based model that considers image degradation as perceived change in structural information, while also incorporating important perceptual phenomena, including both luminance masking and Contrast (vision), contrast masking terms. This distinguishes from other techniques such as mean squared error (MSE) or peak signal-to-noise ratio (PSNR) that instead estimate absolute errors. Structural information is the idea that the pixels have strong inter-dependencies espec ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Perceptual Evaluation Of Video Quality
Perceptual Evaluation of Video Quality (PEVQ) is an end-to-end (E2E) measurement algorithm to score the picture quality of a video presentation by means of a 5-point mean opinion score (MOS). It is, therefore, a video quality model. PEVQ was benchmarked by the Video Quality Experts Group (VQEG) in the course of the Multimedia Test Phase 2007–2008. Based on the performance results, in which the accuracy of PEVQ was tested against ratings obtained by human viewers, PEVQ became part of the new International Standard. (2008) Application The measurement algorithm can be applied to analyze visible artifacts caused by a digital video encoding/decoding (or transcoding) process, radio- or IP-based transmission networks and end-user devices. Application scenarios address |
Data Compression Ratio
Data compression ratio, also known as compression power, is a measurement of the relative reduction in size of data representation produced by a data compression algorithm. It is typically expressed as the division of uncompressed size by compressed size. Definition Data compression ratio is defined as the ratio between the ''uncompressed size'' and ''compressed size'': : = \frac Thus, a representation that compresses a file's storage size from 10 MB to 2 MB has a compression ratio of 10/2 = 5, often notated as an explicit ratio, 5:1 (read "five" to "one"), or as an implicit ratio, 5/1. This formulation applies equally for compression, where the uncompressed size is that of the original; and for decompression, where the uncompressed size is that of the reproduction. Sometimes the ''space saving'' is given instead, which is defined as the reduction in size relative to the uncompressed size: : = 1 - \frac Thus, a representation that compresses the storage size of a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Czenakowski Distance
The Czenakowski distance (sometimes shortened as CZD) is a per-pixel quality metric that estimates quality or similarity by measuring differences between pixels. Because it compares vectors with strictly non-negative elements, it is often used to compare colored images, as color values cannot be negative. This different approach has a better correlation with subjective quality assessment than PSNR. Definition Androutsos et al. give the Czenakowski coefficient as follows: d_z(i,j) = 1 - \frac Where a pixel x_i is being compared to a pixel x_j on the ''k''-th band of color – usually one for each of red, green and blue. For a pixel matrix of size M \times N, the Czenakowski coefficient can be used in an arithmetic mean spanning all pixels to calculate the Czenakowski distance as follows: \frac\sum^_\sum^_\begin1 - \frac\end Where A_k(i,j) is the ''(i, j)''-th pixel of the ''k''-th band of a color image and, similarly, B_k(i,j) is the pixel that it is being compared to. Use ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Structural Similarity Index Measure
The structural similarity index measure (SSIM) is a method for predicting the perceived quality of digital television and cinematic pictures, as well as other kinds of digital images and videos. It is also used for measuring the similarity between two images. The SSIM index is a Video quality#Classification of objective video quality models, full reference metric; in other words, the measurement or prediction of image quality is based on an initial uncompressed or distortion-free image as reference. SSIM is a perception-based model that considers image degradation as perceived change in structural information, while also incorporating important perceptual phenomena, including both luminance masking and Contrast (vision), contrast masking terms. This distinguishes from other techniques such as mean squared error (MSE) or peak signal-to-noise ratio (PSNR) that instead estimate absolute errors. Structural information is the idea that the pixels have strong inter-dependencies espec ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Visual Masking
Visual masking is a phenomenon of visual perception. It occurs when the visibility of one image, called a target, is reduced by the presence of another image, called a mask. The target might be invisible or appear to have reduced contrast or lightness. There are three different timing arrangements for masking: forward masking, backward masking, and simultaneous masking. In forward masking, the mask precedes the target. In backward masking the mask follows the target. In simultaneous masking, the mask and target are shown together. There are two different spatial arrangements for masking: pattern masking and metacontrast. Pattern masking occurs when the target and mask locations overlap. Metacontrast masking occurs when the mask does not overlap with the target location. Factors affecting visual masking Target-to-mask spatial separation Suppression can be seen in both forward and backward masking when there is pattern masking, but not when there is metacontrast. Simultaneou ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
