184results about How to "Resolve blur" patented technology

The invention discloses a margin-oriented self-adaptive image interpolation method and a VLSI implementation device thereof. The method comprises the steps that the gradient magnitude and the gradient direction of a source image pixel are computed, and marginal information is obtained by comparing the gradient magnitude and a local self-adaptive threshold value, wherein the marginal direction is perpendicular to the gradient direction; the marginal direction is classified, filtering is conducted through the marginal information, and an image is divided into a regular marginal area and a non-marginal area; the regular marginal area interpolation is conducted in the marginal direction, and an improved bicubic interpolation method, a slant bicubic interpolation method and a slant bilinear interpolation method based on local gradient information are adopted to conduct image interpolation according to the classification of the marginal information; image interpolation is conducted on the non-marginal area through the improved bicubic interpolation method based on the local gradient information. The VLSI implementation device comprises a marginal information extraction module, a self-adaptive interpolation module, an input line field synchronous control module and an after-scaling line field synchronous control module. The margin-oriented self-adaptive image interpolation method and the VLSI implementation device of the margin-oriented self-adaptive image interpolation method can effectively improve the effect of image interpolation with high-magnification scaling, and is beneficial to integrated circuit framework achieving.

The invention provides an image photographing method and a mobile terminal and solves the problem that an image is blurred due to shake in an existing photographing process. The method comprises the steps of obtaining N preview images collected by a camera and adding the N preview images to an image cache queue; calculating a definition value of a target region of each preview image in the N preview images; and if a photographing instruction is received, determining the preview image with the highest definition value of the target region in the image cache queue as the target image, and outputting the target image, wherein the N is an integer greater than 0. The preview image with the highest target region definition value in the image cache queue is taken as the target image, the problem that the image is blurred due to the shake in the existing photographing process is solved, and the image with the clear target region can be obtained when photographing is carried out.

The invention discloses a method for synchronizing focusing operation and zooming operation. The method for synchronizing the focusing operation and the zooming operation is used for solving the problem that in the prior art, after the shooting object distance is changed due to scene changes, images are fuzzy to a great extent in the zooming process and after the zooming process is accomplished. The method for synchronizing the focusing operation and the zooming operation comprises the steps that in the zooming process, a switching mode for switching zooming tracking curves and a zooming tracking curve are determined, wherein the next cycle of rotation of a zooming motor and a focusing motor is driven according to the zooming tracking curve; the zooming tracking curves are switched, and the zooming motor and the focusing motor are driven to synchronously rotate according to the changed zooming tracking curve. Automatic focusing can be achieved in the zooming process, the situation that after multiplying power of an image is zoomed to form high multiplying power, the image is in a fuzzy state so that the focusing direction of automatic focusing operation cannot be easily judged is avoided, the difficulty of automatic focusing operation is reduced, and the focusing speed is increased.

The invention relates to an infrared image enhancement method for electrical equipment based on non-downsampling shear wave transform. The method comprises the following steps: step S100, establishinga mapping relationship between RGB and gray value of an infrared image; Step S200, performing non-downsampling shear wave transform on the infrared image of the electric equipment obtained in the experiment; S300, calculating the maximum inter-class difference of the infrared low-frequency image of the electrical equipment, obtaining a segmentation threshold between the background and the foreground, and segmenting the low-frequency image into two classes of the environmental background and the electrical equipment; S400, enhancing the low-frequency image, linearly enhancing the low-frequencyforeground electrical equipment, and performing histogram equalization and enhancement on the low-frequency background; Step S500, designing an optimized fuzzy membership function, and carrying out fuzzy enhancement on the high-frequency image of the electrical equipment; Step S600, synthesizing the enhanced low-frequency coefficient and high-frequency coefficient according to the NSST inverse transform into a new electrical equipment infrared image. Compared with the prior art, the invention has the advantages of higher image quality, stronger practicability and the like.

The invention discloses an underwater color image enhancement method integrating dark primary and white balance and belongs to the technical field of image processing. In an underwater environment, scatter and attenuation of light result in low contrast of an underwater color image, color distortion, and serious image quality reduction; an underwater optical imaging model is established; underwater transmissivity and atmosphere light components are estimated according to a dark primary prior rule, the underwater color image is restored and sharpened; and the restored image is subjected to color correction according to a white balance theory, and the underwater color image is enhanced. The underwater color image enhancement method can better enhance image details according to imaging characteristics of the underwater color image; colors are rich, and the method has higher operational speed.

When cameras are developed from film cameras to electronic cameras, a basis is provided for intellectualization of cameras, automatic and intelligent systems are provided at the aspects of focusing and aperture adjustment, however, the time for photographing is still controlled by an operator completely, so that the problems at the aspects of the operation stability and the definition of images collected by cameras exist. The intelligent photographing system and method for obtaining stable imaging thoroughly break through traditional thinking ways in the existing image stabilizing technical field, stable images are not obtained through stabilizing of a camera lens and a charge coupled device (CCD), features of existing photographing devices, which include electronic imaging and digital storage, are used, the time for photographing is selected intelligently, and the time for picture collection and pictures are evaluated, so that clear pictures are obtained.

The invention discloses an enhancement method of an underwater color video image. The method comprises the following steps of: according to a propagation characteristic of visible light in water, light composition on an image surface and an expected target, establishing an underwater optical imaging model; according to a priori rule of a dark primary color, estimating an absorption function t (x, y) and a scattering parameter A of the underwater optical imaging model, and restoring the underwater color video image I into an image J; and according to an image enhancement processing method based on the Retinex theory, enhancing the image J. According to the invention, the dark primary color priori rule and the image processing method based on the Retinex theory are combined for the first time, firstly restoration processing is carried out according to the underwater optical imaging model to remove fuzzy noise caused by scattering, then enhancement processing is carried out to sharpen the details and adjust the color deviation, and compared with a previous realization method of adopting pure restoration or enhancement, the method of the invention has better robustness.

The invention discloses a method of detecting and recognizing a target by using a police video monitoring fuzzy image. A Kalman filtering method and a rectangle tracking method are combined, and target position and area features are separated; through constructing a feature recognition matrix, the motion state of the target is analyzed; and corresponding multi-angle of view monitoring tracking is executed on different states. As for the police video monitoring fuzzy image, a fuzzy neural network and an RS theory are adopted, the target is detected and recognized, a new algorithm is improved and put forward, and the fuzzy image recognition rate is improved; effective information is subjected to fusion processing, the features of the target object are dynamically extracted, and dynamic capturing and early warning are carried out, and the advanced level of the country is reached; and the problem that the current video monitoring image is fuzzy can be solved.

The invention discloses an underwater image enhancement method based on a foreground model. The method comprises the following steps that: improving a background light estimation method so as to effectively avoid the influences of underwater image overexposure, artificial light sources and the like; combining with the cognition of people for the underwater image, and utilizing a dark channel priori algorithm to remove background scattering and extract the foreground model; and combining with a white balance algorithm to put forward a color correction method suitable for the underwater image, and utilizing the attenuation characteristic of light in water to correct channel gains according to a relationship between channel attenuation coefficients so as to compensate color distortion caused by attenuation; and utilizing the channel gains to regulate a fogless image, and finally, obtaining the enhanced underwater image. By use of the method, the enhancement effect of an object part is clear and distinct, and a visual effect is better; image blurring is effectively removed, so that the definition of the enhanced underwater image is greatly improved, image details are better, the image enhancement of the background part is not affected on the basis of the color correction of the foreground model, the enhanced underwater image has more natural integral colors, and image brightness is within an acceptable range.

The invention relates to the field of magnetic resonance imaging technique, in particular to a magnetic resonance fast spin echo (FSE) imaging method, comprising the steps as follows: 1. phase coding gradient amplitude is reset, pre-scanning is carried out by FSE pulse sequence, the amplitude value of each etch signal peak on the echo chain is recorded; 2. the phase and inclination angle of convergence pulse is adjusted so as to lead the amplitude of each echo signal peak on the echo chain to achieve the maximum value, when the amplitude value Am and phase angle Phim of each echo signal peak are recorded; 3. the phase coding gradient is recovered, the scanning is carried out by the FSE pulse sequence, thus gaining the K space data; 4. according to the amplitude Am and Fai<m> of each echo signal peak gained in step 2, the K space data is corrected; 5. image reconstruction is carried out by the corrected K space data thus gaining the magnetic resonance images, etc. The magnetic resonance fast spin echo (FSE) imaging method solves the problems of echo amplitude phase oscillation and image blurring due to transverse relaxation of the prior art.

The invention discloses a satellite health state multistage fuzzy evaluation method based on an AHP-entropy weight method. The method includes: constructing a system weight system comprising a subjective weight, an objective weight and a comprehensive weight, providing the accurate comprehensive weight for the fuzzy comprehensive evaluation method by adopting an analytic hierarchy process and an entropy weight method, providing the subjective weight by adopting the analytic hierarchy process, providing the objective weight by adopting the entropy weight method, and obtaining the subjective andobjective combined comprehensive weight from the subjective and objective weights through an optimization function; constructing a system evaluation system comprising a factor discourse domain, a comment set, a membership function, an evaluation matrix and multi-stage fuzzy evaluation; and comprehensively evaluating the use state of the on-orbit satellite, evaluating each layer of elements through a membership principle of fuzzy comprehensive evaluation, and then sequentially recursively evaluating the overall health state from bottom to top by adopting a multi-stage fuzzy comprehensive evaluation method. The method improves the safety and reliability of a satellite system, reduces the effective life cycle operation cost, and guarantees the smooth completion of an in-orbit satellite task.

The invention discloses a quick full-waveform inversion method for edge guide and structural constraint. The edge of a model is detected by using a canny operator, namely, velocity and interface are inverted at the same time in full-waveform inversion, and then holding structural regularization and structure constraint regularization are carried out on the gradient of residual of the model through bilateral filtering. The problem that the edge information and structure information are fuzzy for a conventional full-waveform inversion method is solved. Moreover, damage to the model result and boundary in the high-noise de-noising process is overcome, and the inversion result structure and boundary information are enhanced.

The invention provides a method and a device for enhancing image definition based on zoom factor, aiming to solve the problem that the existing image definition enhancement technology can not effectively treat image zoom. The invention can effectively enhance the image definition when input images are zoomed. The method for enhancing the image definition based on zoom factor comprises the following steps: obtaining the frequency component of the attribute value of pixel to be treated through filtering which adopts low-pass filtering or band-pass filtering; carrying out transient enhanced treatment on the frequency component obtained from the step; and merging the frequency component after the transient enhanced treatment and other separated frequency components so as to realize image definition enhancement. The method adjusts the image definition enhancement according to the image zoom factor, thereby solving the problem of the prior art, and effectively treating image definition enhancement when the images are zoomed.

The invention provides an InISAR imaging method based on double-frequency conjugation processing and discloses a method in which the double-frequency conjugation processing technique is combined with the interferometric technique to be applied to ISAR so as to achieve moving object positioning and imaging. The method comprises the steps of conducting sub-band segmentation, conducting sub-band pulse compression and double-frequency conjugation processing, conducting rough interferometric measurement on a target with composite signals, conducting original signal imaging and interferometric processing, and achieving target scattering point accurate measurement through the combination of the interference result of an original signal image and the result of rough interferometric measurement to further achieve target positioning and imaging. The method mainly solves the problem of target Doppler frequency blurring and target interferometric measurement blurring in an InISAR mode and can achieve target positioning and imaging at the same time.

The invention belongs to the technical field of image processing and provides an environment self-adaptation video image de-noising method and device. The method includes the steps that statistics is performed on the average brightness of video images under different illumination intensities, and a time domain de-noising threshold and a space domain de-noising threshold are determined; the average brightness of the images is calculated according to the currently acquired video images, and the current time domain de-noising level and the current space domain de-noising level are determined according to the time domain de-noising threshold and the space domain de-noising threshold; time domain de-noising is performed on the video images according to the time domain de-noising level; space domain de-noising is performed on the images processed through the time domain de-noising according to the space domain de-noising level. According to the environment self-adaptation video image de-noising method and device, the noise level of the video images can be evaluated by performing statistics on the illumination degree of the actual environment, time domain de-noising and space domain de-noising can be supported at the same time, de-noising can be dynamically started or stopped or the de-noising level can be adjusted according to the image noise level, and thus a good de-noising effect can be achieved, and the problems that de-noised images are fuzzy and smearing happens to moving objects are well solved.

The invention discloses a method and a device for video zooming and relates to the field of communication network techniques. The method and the device for video zooming solve the problem that a high-resolution video cannot be zoomed in when the high-resolution video is played in low-resolution mobile communication equipment in the prior art, and also solve the problems that a low-resolution video cannot be zoomed out and the image of the video is obscure when the low-resolution video is played in high-resolution mobile communication equipment. When a first video is displayed, a first operation is received, and a contact point is determined according to the first operation; zooming multiples of the first video are determined according to a received second operation; the first video is zoomed according to the zooming multiples of the first video to obtain a second video; when a second size is greater than a first size, a third video is obtained and displayed according to the contact point, the first size and the second video; when the second size is not greater than the first size, the second video is displayed. The method and the device for video zooming, provided by the embodiment of the invention are applicable to zooming of played videos.

An embodiment of the invention discloses virtual reality equipment and a lens adjusting method for the same. The virtual reality equipment comprises a photographic module, a processor and a lens control module, wherein the photographic module is used for photographing an eye image of a user, and transmitting the eye image to the processor; the processor is used for calculating a pupil distance of the user and a moving distance of two lenses according to the eye image, and transmitting a calculation result and a control instruction to the lens control module; and the lens control module is used for adjusting the position of each lens according to the calculation result and the control instruction, so that centers of the two lenses are overlapped with centers of pupils of two eyes of the user in a one-to-one correspondence manner. The virtual reality equipment and the lens adjusting method for the same solve the problem that the experience effect is influenced by the blur effect when the user is watching an image due to poor adjustment precision since the VR equipment in the prior art needs to adjust the positions of the lenses manually.

The invention discloses a joint target detection method and device based on a video frame and a pulse array signal. The method comprises the following steps: taking the video frame and the pulse arraysignal as input of target detection; performing self-adaptive division on the continuous pulse array signals; performing synchronous fusion or asynchronous fusion detection according to the relationship between the video frame frequency and the pulse array signal division frequency; fusing the video frame and the pulse array signal in a feature expression form; outputting a detection result. According to the invention, the high time resolution and high dynamic capability of the pulse array signal can be effectively utilized to provide the target detection precision of the traditional camera,and especially, the detection problems of high-speed motion blur, overexposure or low illumination and other scenes are solved. The method has wide application potential in the fields of unmanned visual inspection and navigation, unmanned aerial vehicle cruising and positioning, robot visual navigation, video monitoring and the like which relate to high-speed motion.

The invention discloses a photographing method and device. The photographing method comprises the steps that signal transmission medium information of a current photographing environment is obtained, and transmission speed of ultrasonic wave signals in the current photographing environment is determined according to the signal transmission medium information of the current photographing environment; the distance between a photographed target and a photographing terminal is obtained according to time for transmitting the ultrasonic wave signals of an ultrasonic wave sensor in the photographing terminal, time for receiving ultrasonic wave reflection signals and the transmission speed of the ultrasonic wave signals in the photographing environment; focusing is carried out according to the distance between the photographed target and the photographing terminal. The method solves the problem that in the prior art, as the photographing environment changes, photographing focusing is inaccurate.

The invention relates to a regenerative braking control system and method of an active electric vehicle. The regenerative braking control system comprises an information acquisition unit, an information interaction unit, an information parsing unit and a control unit, wherein the information acquisition unit is used for acquiring vehicle information, the information interaction unit is used for receiving feedback information of a driver to achieve person-vehicle information interaction, the information parsing unit is used for parsing the vehicle information acquired by the regenerative braking control system, the control unit is used for obtaining the braking intention of the driver according to the obtained parsed vehicle information and providing corresponding control parameters according to the braking intention to control the braking situation of an electric vehicle, the information acquisition unit and the information interaction unit are connected with the information parsing unit, and the information parsing unit is connected with the control unit.

The invention discloses a control method and device for panoramic photography exposure. The method comprises the following steps: starting panoramic photography; obtaining actual angular speed of current movement of a mobile terminal; according to the actual angular speed, a preset angular speed and the exposure time for guaranteeing an image not to be fuzzy when the mobile terminal moves at the preset angular speed, adjusting preset exposure time and gain; controlling photography exposure according to the adjusted exposure time and gain. The exposure time and the gain are adjusted according to the actual angular speed of the mobile terminal during movement, the higher the actual angular speed is, the shorter the adjusted exposure time is and the larger the adjusted gain is, the definition of the image is guaranteed, and the lower the actual angular speed is, the longer the adjusted exposure time is, the smaller the adjusted gain is and the smaller the image noise point number is, so that a problem of image fuzziness can be solved and noise points can be optimized.