389 results about "Objective quality" patented technology
Filter
Efficacy Topic
Property
Owner
Technical Advancement
Application Domain
Technology Topic
Technology Field Word
Patent Country/Region
Patent Type
Patent Status
Application Year
Inventor
Quality objectives are goals for the value of products, services and processes. It is a basic quality management process to establish a set of quality objectives. Unlike a quality policy, that is set at the top level of an organization, quality objectives can be specific to a department, team, process or project.
The invention discloses an all-reference three-dimensional image qualityobjective evaluation method based on visual salient feature extraction. According to the method, a left view and a right view of a three-dimensional image pair are processed to obtain a corresponding disparity map; image fusion is performed on the left view and the right view of the three-dimensional image pair to obtain an intermediate reference image and an intermediate distortion image; a spectral residual visual saliency model is utilized to obtain a reference saliency map and a distortionsaliency map, and a visual saliency map is obtained through integration; visual information features are extracted from the intermediate reference image and the intermediate distortion image, and depth information features are extracted from the disparity map of the three-dimensional image pair; similarity measurement is performed to obtain measurement indexes of all the visual information features of vision saliency enhancement; and support vector machine training prediction is performed, an objective qualityscore is obtained, mapping of three-dimensional image quality is realized, and measurement and evaluation of three-dimensional image quality are completed. Through the method, image quality objective evaluation and subjective evaluation have good consistency, and the performance is superior to that of existingthree-dimensional image quality evaluation methods.
The invention discloses an objective evaluating method for the audio quality of streaming media, which comprises: acquiring original audio at a transmitter and acquiring distorted audios into which a coder, a decoder, package lost and delayjitter impairment are introduced after network transmission; performing pretreatment and module alignment treatment on distorted audios with a network characteristic, performing perceived evaluation of audio quality (PEAQ) and outputting the distorted audios of which delay and jitter are eliminated; performing coder and decoder and packet lost impairment quality evaluation on the original audio and aligned distorted audio; for impairment caused by delay and jitter between the distorted audios and the aligned audios, performing objective quality evaluation by network impairment estimation; and fitting the quality evaluation values of the two kinds of impairment to obtain the objective evaluation values of the original audios and the distorted audios transmitted by the network.
The invention discloses a no-reference image quality evaluation method based on a fully convolutional neural network. A full reference image quality evaluation method is adopted to obtain the objective and real quality map of each distorted image in a training set as supervision to train the normalized image of all distorted images in the training set, and an optimal fully convolutional neural network regression training model is obtained; the normalized image of the distorted image to be evaluated is input into the optimal fully convolutional neural network regression training model; the objective quality evaluation prediction quality map of the distorted image to be evaluated is predicted; and the saliency map of the distorted image to be evaluated is used for carrying out weighted pooling on the objective quality evaluation prediction quality map so as to obtain an objective quality evaluation prediction value. Since various features, including full reference features, saliency features and the like, of the distorted image are combined and the features can accurately describe the distorted image, dependency between the objective evaluation result and subjective perception is effectively improved.
The invention provides loop wave filtering method and device, wherein the method comprises the following steps: a. acquiring a macro block which needs loop wave filtering; b. detecting the sub-block mode of the current macro block and extracting the wave filtering intensities of the edges of a corresponding sub-block; setting the wave filtering intensity of the internal edge of the sub-block intozero; and c. carry out wave filtering on the current macro block according to the acquired wave filtering intensities of different edges. The invention improves the extraction process of wave filtering intensity, and reduces requirements of a loop wave filtering process on system resources; therefore, on the premise of ensuring the subjective effect and the objective quality of code images, the invention simplifies the loop wave filtering process and reduces the requirements of the process on the system resources.
The invention relates to the field of video decoding, in particular to a parameter-adaptive multidimensional bit rate control method based on video content characteristics. The method comprises the following steps: determining an initial coding frame rate according to a channel bandwidth and an initial frame complexity of a video sequence; determining a model parameter update cycle according to a dynamically transformed video, and extracting a video time-space complexity from a sliding window of the current update cycle; meanwhile, determining the length of the next update cycle by combining the bit rate control accuracy of the current update cycle, and updating the multidimensional bit rate control model parameters and the coding parameters. The parameter-adaptive multidimensional bit rate control method based on video content characteristics is superior to internationally similar relevant methods, can effectively improve the subjective quality and objective quality, especially for the video sequence with high time-space complexity, and can slightly reduce the computational complexity.