175 results about "Ringing effect" patented technology

The subject invention reveals improvement methods for circuits that use a coupled inductor wherein overshoot and ringing associated with leakage inductance of said coupled inductor is entirely eliminated by addition of non-dissipative active clamp networks that clamp each winding during each operating state of a power supply containing said coupled inductor. A further improvement applicable to zero voltage switching circuits that employ an inductor for driving a zero voltage turn on switching transition of a switch enables elimination of said inductor and preserves said zero voltage switching properties by adding leakage inductance to a coupled inductor without any adverse overshoot and ringing effects associated with said leakage inductance. The subject invention also reveals a coupled inductor with enhanced leakage inductance which can be used with said other improvements. Example circuits including zero voltage switching flyback and forward converters which require only one magnetic circuit element are revealed. Zero voltage switching tapped inductor buck and boost converters with a single magnetic circuit element are also revealed.

The invention relates to a sparse representation-based blind restoration method of a broad image, aiming at solving the technical problem that an image restored by the existing broad image blind restoration method is bad in effect. The method has the technical scheme that the broad image is sparsely represented by a fuzzy dictionary and a brilliant image is rebuilt by a brilliant dictionary to restore the image due to the characteristic that the sparse coefficient of the broad image under the fuzzy redundancy dictionary is coincident with that of the brilliant image under the brilliant redundancy dictionary. The illcondition during deconvolution can be avoided, the ringing effect at a high edge during image restoration can be reduced, and the image which is more brilliant can be obtained.

The invention discloses image reference-free quality evaluation method and system based on a gradient profile. The image reference-free quality evaluation system comprises a gradient profile extraction device, a blurring effect evaluation device, a ringing effect evaluation device and an integrated evaluation device, wherein the gradient profile extraction device is used for detecting input image edge points and extracting the gradient profile according to the edge points; the blurring effect evaluation device is used for measuring the blurring effect of images according to the gradient profile; the ringing effect evaluation device is used for measuring the ringing effect of the images according to the gradient profile; and the integrated evaluation device is used for fusing the blurring effect measurement and the ringing effect measurement to acquire a quality evaluation reference value of input images. Based on the invention, the quality evaluation can be carried out on various types of natural images; and especially, the invention has favorable robustness for partially-blurred images due to the defocusing, the motion and other reasons.

The invention provides an image restoration method of a blurred image. The method comprises steps of: S100 acquiring a blurred image, converting the blurred image and the corresponding target blurred core from the time domain to the frequency domain, and dividing the blurred image into a plurality of blurred sub-image blocks; S200 with the preset blurred core algorithm, estimating the target blurred core of each blurred sub-image block at the same time; S300 according to the preset image restoration algorithm combined with the target blurred cores, calculating and obtaining clear sub-image blocks; S400 jointing and merging each clear sub-image block according to the order of each blurred sub-image block to obtain a clear image corresponding to the blurred image. The method can rapidly estimate the blurred core, can obviously reduce the ringing effect caused by the deconvolution operation, and improve the precision of the deconvolution algorithm.

The invention discloses a super-resolution reconstruction algorithm based on improved neighborhood embedding and structure self-similarity, comprising the following steps: first, the neighborhood embedding method is improved by use of structure similarity, more accurate high-frequency initial estimation is obtained, and an initial estimation algorithm based on neighborhood embedding is realized; and then, the local self-similarity and multi-scale structure similarity of a low-resolution image are used to construct a reconstruction constraint for the purpose of reconstructing high resolution, and a sparse representation dictionary is established. Compared with the prior art, on the basis that the algorithm put forward by the invention solves the problem that the learning-based super-resolution reconstruction algorithm of predecessors needs a lot of training sets, the neighborhood embedding method is improved, the method is adopted to solve the problem of inaccurate high-frequency initial estimation in a super-resolution algorithm based on local self-similarity and multi-scale similarity, and the super-resolution reconstruction effect of images is enhanced; and the saw-tooth effect and the ringing effect are suppressed better, and a reconstructed high-resolution image is closer to the real image and is of better subjective and objective quality.

The invention relates to a real video recovery method based on local strategies and belongs to the field of image processing and pattern recognition. The real video recovery method based on the local strategies is characterized by comprising, firstly, extracting the moving foregrounds of the neighboring two frames of a real video, matching the feature points of the moving foregrounds and accordingly estimating the blurring kernels of every pixel point in the foregrounds; secondly, for eliminating object motion blur of space change inside the video, providing an ADM (adaptive delta modulation) algorithm, namely, recovering all the overlapped local blocks and integrating the local blocks into clear video frames. The real video recovery method based on the local strategies can overcome the deficiencies of amplifying noise and introducing ringing effects in traditional methods and achieve good recovery effects on the edges and the details of the video frames.

The invention relates to a visual saliency-based image deblurring method. The method is characterized in that according to a visual attention mechanism, saliency dividing is carried out on a to-be-processed image by utilizing image sharpness as a saliency condition, wherein the saliency dividing includes division of a saliency portion and a non-saliency portion; blurring kernel estimation is carried out on the non-saliency portion so as to obtain a blurring kernel K of the image; and a compensation mechanism is introduced and thus the obtained blurring kernel is applied to the whole to-be-processed image, and a ringing-free effect occurs at the edge of the saliency portion so as to obtain an image processed by deblurring. According to the method provided by the invention, as the visual attention-based saliency study, the blurred image is divided into two portions including the saliency portion and the non-saliency portion based on a saliency map; only the blurring kernel of the non-saliency portion is estimated and that is, the blurred portion of the blurred image is processed so as to maintain the clear portion. Therefore, the influence on blurred images with different blurring degrees of different portions and different blurring directions due to the same blurring kernel estimation processing can be eliminated.

A method and apparatus for enhancing the video quality of compressed video signals adaptively removes distortions and ringing effects embedded in the decompressed images. The apparatus operates in conjunction with decoder devices installed in set-top boxes, satellite receivers, TV broadcast channel servers, digital still cameras, DVD players and recorders, large screen TV sets, media players, and the like.

The present invention relates to a method for eliminating a blocking effect in a compressed video signal signal. The method of the invention includes: the encoding step of eliminating a blocking effect by compensating the motion of a signal compressed in block unit to be transmitted; the decoding step of restoring the motion compensated video signal to the original video signal by reducing the prediction residual between the motion compensated video signal and the original video signal and the blocking effect; and the post-filtering step of performing post-filtering in a blocking elimination filter in order to eliminate a blocking effect and ring effect remained in the compensated signal. The equation for obtaining the original pixel is made simple by eliminating the remaining blocking effect and ring effect using a loop/post filter. In addition, normalization parameters can be stored in the look-up table and can be detected according to the difference between pixels adjacent to the original pixel and the size of quantizaiton, whereby the equation for restoring the compressed moving video signal, resulting in excessive smoothing, becomes simpler, and filtering control is made possible by a simple equation, thus making a high speed real time video signal processing possible.

The invention discloses a satellite remote sensing space-time distribution inversion algorithm for column concentration of polluted gas. The satellite remote sensing space-time distribution inversionalgorithm comprises the following steps: selecting a spectral waveband and a resolution ratio; carrying out difference absorption spectrum analysis method inversion; carrying out contrast verificationon ground-based observation and a chemical model simulation result. The satellite remote sensing space-time distribution inversion algorithm for the column concentration of the polluted gas has the advantages that 1) the quantity/position of detected damaged pixels is judged and identified through fitting residuals and the signal-to-noise ratio of a detector is calculated; 2) key parameters including a slit function, spectrum drifting and the like, which are changed in real time after the simulated detector is launched into the sky, can be realized, the inversion errors are reduced and the inversion precision is improved; 3) overlapping influences on different trace gas spectrums in fitting calculation and influences on atmosphere ring effects are eliminated; 4) the satellite remote sensing space-time distribution inversion algorithm can be applied to an atmospheric pollution gas absolute total amount inversion algorithm of ground-based and onboard observation; 5) an actual atmospheric outline of China is combined with land surface emissivity and a detector posture to construct an atmospheric quality factor lookup table which is changed along wavelength.

The invention discloses an image motion blur blind removing method based on gradient domain and depth learning, A guide filter gradient domain image is used as a basic image, A L0 filt gradient domainimage and a corresponding clear image are taken as samples, that clear image is randomly convolution with different blur kernel, and 1% Gaussian white noise is added to generate a motion blur image.The gradient domain image after the guide filter, the gradient domain image after the L0 filter and the motion blur image constitute a training data set; The depth convolution neural network is constructed, and the weight data of the depth convolution neural network is learned from the training data set, and the depth convolution neural network used for motion fuzzy kernel estimation is learned. Extracting the weight data of the network training, obtaining the motion blur kernel, optimizing the deconvolution function of the image prior constraint, and obtaining the motion blur image by using the total variational term. This method can effectively suppress the image ringing effect and reduce the image noise, and the effect of motion blur removal is better.

A super-resolution reconstructed image quality Contourlet domain evaluation method comprises the steps of respectively performing non-downsampling Contourlet transformation on an original low-resolution image and a super-resolution reconstructed image to obtain directional sub-band coefficient images of a transformation domain; utilizing directional entropy to calculate sub-band image energy distribution, evaluating the increase degree of detail information of the super-resolution reconstructed image with energy distribution change degree as the standard, wherein the increase degree of the detail information of the super-resolution reconstructed image is marked as a reconstruction entropy factor; dividing pixels in the reconstructed image into strong edge pixels, weak edge pixels and noise pixels according to characteristics of the Contourlet coefficients, evaluating the severity degree of the ringing effect, for the strong edge pixels, according to the coefficient change in neighborhood domains of front and rear edge pixels to obtain a ringing factor, and evaluating the fuzzy degree of the weak edge pixels to obtain a fuzzy factor; fusing the entropy factor, the ringing factor and the fuzzy factor to obtain the unified quality evaluation standard.

The invention relates to a turbulence-degraded image blind restoration method based on dark channel and Alternating Direction Method of Multipliers. The method includes the following steps: firstly on the basis of the multiple dimension theory, in each dimension, applying dark channel prior constraint on an image, applying sparse constraint and energy constrain on a point spread function, then using the coordinate descent method and conducting alternating iteration to estimate a fuzzy kernel and the image in current dimension, if the dimensions arrive at the maximum thereof, a final estimated fuzzy kernel is obtained, finally, in combination with a total variation model, using a derivative Alternating Direction Method of Multipliers to make details of the image restored quickly. According to the invention, the method, by using the dark channel prior information of a clear image as a constraint item, can help a cost function to converge to a clear solution in the iteration process, addresses the susceptibility of obtaining a fuzzy solution by using tapered prior information under the Maximum posterior probability in current blind restoration algorithm, such that the method herein can restore more image details, has less ring effect, and effectively increases restoring quality.

The invention discloses a steel tube UV-curing color-painting mechanism. A cylinder and a guide rail of a linear guide rail pair are horizontally arranged on a cantilever beam bracket. A piston rod end of the cylinder and a sliding block of the linear guide rail pair are respectively fixedly connected with a lifting cylinder support, the lifting cylinder support horizontally is driven to move long the linear guide rail through the retraction of a piston rod of the cylinder; the cylinder body of a lifting cylinder is fixedly connected with the support, a piston rod end of the lifting cylinder are fixedly connected with a rubber roll color-painting device, the rubber roll color-painting device is driven to move vertically through the retraction of the piston rod of the lifting rod; and a UV lamp shade is arranged on a steel tube. When the UV-curing color-painting mechanism works, ink (paint) is evenly printed on the steel tube after transferred through an anilox roller, a distributor roller and an offset printing roller to form a color ring. By adopting a principle of curing UV ink (paint) by UV, the color ring painted on the steel tube is instantly dried, thus the working efficiency and the color ring effect are greatly improved. Especially, the invention avoids the drop of corrosion resistant coating because color ring coating is not dried fully to influence the UV corrosion resistance.

An image display device includes a smoothing unit that filters the image data to be displayed. According to one aspect of the invention, only bright parts of the image that are adjacent to dark parts are smoothed, thereby improving the sharpness of dark dots and lines displayed on a bright background. According to another aspect, different primary colors are smoothed with different characteristics, enabling unwanted colored tinges to be removed from the edges of white areas. According to still another aspect, smoothing moves the luminance centroids of all primary colors in a direction in which the display screen is scanned, to reduce ringing effects without needless loss of edge sharpness.

The invention provides a spatial variation point diffusion function smoothing method based on simple lens calculating imaging. The method is characterized by fully using characteristics of sparsity, similarity and the like of a single lens fuzzy kernel; firstly, using a blind convolution algorithm to estimate a fuzzy kernel of each image block, and combining fuzzy kernel TV priori; and then carrying out smoothing and de-noising processing on the fuzzy kernel, and based on a filtered PSF of neighborhood information, replacing an existing PSF. Compared to the prior art, by using the method of the invention, a complex experiment environment and equipment are not needed, the spatial variational PSF can be estimated through combining a correlation algorithm based on a simple lens system; robustness of a deconvolution process is increased; and a noise, a ringing effect and the like are restrained.

A method and apparatus to remove a block effect and a ring effect appearing in a compression-coded image is disclosed. The present invention is especially applicable to an image compression-coded at a low bit rate. In particular, the present invention includes a variety of masks for the removal of the block/ring effect. Thus, one mask is select for a pixel to be filtered. Moreover, candidate pixels to be averaged with the pixel to be filtered is selected from the pixels of the selected mask to better maintain the details of the image, and a weight is applied to improve the calculation speed of the averaging operation. More particularly, the masks according to the present invention have longer tabs toward adjacent blocks at boundaries of the given block to remove the block and ring effect.In the method, a pixel of an image is filtered according to a filtering methodology. The filtering methodology includes more than one comparison, and each comparison compares a respective determined value and a respective threshold. At least one of the respective thresholds may be based on quantization information of at least a portion of the image including the pixel. Each respective determined value may be based on a respective difference value, and each respective difference value may be based on a different difference. At least one the difference values may be based on the pixel being filtered and another pixel.

The invention discloses a blind deblurring method for image quality evaluation, and mainly solves the problems of distortion and scratches which are produced in the iterative deblurring process of most images. The blind deblurring method comprises the following steps: (1) initializing a blurring kernel vk into a Gaussian pulse function, initializing an evaluation image yk into a blurred image z, setting an initial iteration index k=0, and setting the maximum number of iterations kmax; (2) solving the image yk and denoising the image yk; (3) performing quality evaluation on the image yk, if the quality evaluation value is the current minimum value, storing the yk and setting the yk as an optimal image yA, otherwise solving the blurring kernel vk and denoising the blurring kernel vk; (4) setting k=k+1, if k>kmax, performing step (5), otherwise returning to the step (2); and (5) convolving the image yA by a Gaussian function H to obtain an image yB, and performing non-blind deblurring on the yB by using a total variation iteration method to obtain the final deblurred image F. By using the blind deblurring method, a clear image can be recovered; the ringing effect and distortion are reduced; scratches of the image, which are caused in the iteration process, can be repaired; and the method can be used for performing blind deblurring on various blurred images.

The invention discloses an image super-resolution method based on dictionary learning and non-local total variation. The image super-resolution method based on the dictionary learning and the non-local total variation mainly solves the problems of ring effect, lost high-frequency information, and inaccuracy of boundary matching of a super-resolution method and the like. The achieving steps include (1), inputting an image training set; (2) using a KSVD algorithm to train two corresponding high-resolution dictionary and a low-resolution dictionary; (3) conducting sparse representation of a low-resolution input image, and determining sparse coefficient; (4) using determined sparse coefficient and the high-resolution input image to obtain a high-resolution image; (5) conducting ring effect removal of the non-local total variation on the reconstructed high-resolution image; (6) conducting high-frequency information enhancing of the high-resolution image by error compensation, and obtaining a final result. By showing of a simulation experiment, compared with the prior art, the image super-resolution method based on the dictionary learning and the non-local total variation has the advantages of being simple in operation, small in noise, clear in edge and the like, and can be used for obtaining a high-definition image.

The invention refers to an airborne ultrasound testing system for test object (3) containing an ultrasound generator (1,9), an ultrasound receiver (2), a controller for both and a computer assisted test result interface to display an image of a tested test object (3). The ultrasound generator (1) is a resonance-free thermo-acoustic ultrasound generator which does not rely on mechanically deformable or oscillating parts and the ultrasound receiver (2) is a membrane-free optical microphone in an air or gas coupled pulse-echo arrangement or in an air or gas coupled transmission mode arrangement. With this testing system, it is possible to test objects with high precision and without liquids or disturbing ringing effects.

The invention discloses an image blind deblurring method based on a dark channel prior and a multi direction weighted TV(total variation), which mainly comprises steps of constructing an image blind restoration model and its solution, and finally obtaining a target image and a fuzzy kernel. The method of the invention aims at the problem that the total variation (TV) regularized image restorationhas the limited detail recovery capability and is sensitive to noise. In the method, multi-directional edge detection is utilized, the conventional TV model is improved, and a multi-direction weightedTV model based on edge detection is obtained; at the same time, in order to make the recovery model more universal and improve the detail recovery capability, the dark channel priors is fused into the above multi-direction weighted TV model. Experiments show that the target image restored by the method of the present invention has a perfect visual effect, the local smoothness of the image is maintained, the details such as the edge and texture of the image can be well restored, the ring effect is significantly reduced, and the fuzzy kernel estimation is more accurate.