88 results about "Exposure fusion" patented technology

The invention provides a multi-lens panoramic stitching control method and a multi-lens panoramic stitching control device. The panoramic stitching control method comprises the following steps: firstly, a multi-channel video of a panoramic camera is read, focal length and an included angle of each lens are regulated by a motor according to vision scope and monitoring distance to be monitored to ensure that a part of superposed area is arranged between adjacent pictures. And then, after the focal length is adjusted, the included angle between lenses is correspondingly regulated to carry out space matching alignment onto a superposed video sequence, and effect of forming a large-viewing-angle high-solution continuous image containing video sequence information is realized through exposure fusion.

An apparatus and method for generating a High Dynamic Range (HDR) image from which a ghost blur is removed based on a multi-exposure fusion. The apparatus may include an HDR weight map calculation unit to calculate an HDR weight map for multiple exposure frames that are received, a ghost probability calculation unit to calculate a ghost probability for each image by verifying a ghost blur for the multiple exposure frames, an HDR weight map updating unit to update the calculated HDR weight map based on the calculated ghost probability, and a multi-scale blending unit to generate an HDR image by reflecting the updated HDR weight map to the multiple exposure frames.

A method and an apparatus for image filtering are described. Structural information is employed during the calculation of filtering coefficients. The structural information is described by the regions defined through an edge map of the image. In one embodiment, the region correlation between the target pixel and a contributing pixel is selected as a structural filtering coefficient. The region correlation, which indicates the possibility of two pixels being in the same regions, is calculated by evaluating the strongest edge cut by a path between the target pixel and a contributing pixel. The structural filtering coefficient is further combined with spatial information and intensity information to form a spatial-intensity-region (SIR) filter. The structural information based filter is applicable to applications such as denoising, tone mapping, and exposure fusion.

The invention discloses a single-frame high-dynamic imaging method based on a convolutional neural network. The method comprises the following steps: constructing an enhancement module; constructing an initial convolutional neural network with an enhancement module according to the enhancement module; training the initial convolutional neural network to obtain a trained convolutional neural network; and processing the original single-frame low-dynamic image through the trained convolutional neural network to generate a high-dynamic image. According to the method, the high-dynamic image can bedirectly generated from the single-frame low-dynamic image, the problem that multiple frames of exposure images cannot be obtained at the same time by a moving video in multi-exposure fusion is solved, parameter adjustment is not needed, and the method is convenient to use.

The invention relates to an image processing method and system based on the multi-exposure fusion and the backtracking algorithm. The image processing method based on the multi-exposure fusion and the backtracking algorithm comprises the following steps: obtaining the original image data in the high dynamic photographing mode; performing coarse positioning on the original image data by means of the backtracking algorithm and obtaining a key frame; performing accurate positioning on a number of image frames starting from the key frame by means of the Euclidean distance, and obtaining the optimal image data; judging whether the optimal image data is obtained completely or not; if not, returning to the step of performing coarse positioning on the original image data by means of the backtracking algorithm and obtaining the key frame; if so, performing image fusion on the optimal image data by means of the multi-exposure fusion algorithm, and obtaining the fusion image data combined with the Laplasse product processing. By means of the image processing method and system based on the multi-exposure fusion and the backtracking algorithm, the dynamic folding and the artifact problem caused by the arm jitter is effectively restrained, the edge blur problem is eliminated, the processing speed of the data is improved, the real-time performance of the HDR photographing is ensured, and the appearance of black screen and dead machine under the pressure test of the camera is avoided.

The invention provides a double exposure fusion method and device for an image. The double exposure fusion method for the image comprises the steps of performing human face control point recognition on an original face image, and obtaining a face region graph; performing brightness filling on the face region graph, and obtaining a face weight graph; performing weight fusion on the face weight graph and a single-channel image of the original face image, and obtaining a fusion weight graph; performing soft light processing on the original face image and an original background image, obtaining a soft light processing graph, performing color filter processing on the original face image and the original background image, and obtaining a color filter processing graph; performing fusion processing on the soft light processing graph and the color filter processing graph, and obtaining an image to be fused; and performing fusion processing on the original face image and the image to be fused according to the fusion weight graph, and obtaining a double exposure fusion image. According to the double exposure fusion method provided by the invention, the double exposure effect of the face image in the double exposure fusion image is better through the above manner, so that the double exposure fusion image is more nature.

The embodiment of the invention relates to the field of image processing, and discloses a shooting method, system and device, electronic equipment and a storage medium. In a part of embodiments of theinvention, the shooting method comprises the following steps: determining N areas needing to be exposed in a scene; Respectively exposing each area, and when each area is exposed, shooting a pictureof at least one scene; And carrying out exposure fusion on the shot photo to obtain a final scene photo. In the implementation process, photos of which each area needing to be exposed is exposed are shot, the shot photos are subjected to exposure fusion, and a final photo is obtained, so that the final photo is closer to an image of the effect of a real scene seen by human eyes.

Provided is an image fusion method, device and unmanned aerial vehicle. The method comprises following steps: performing bit plane layering on an original image of a frame to obtain a plurality of bitplanes of the original image, wherein the bit number of the original image is M, and M is an integer greater than 1; obtaining a plurality of frames of reconstructed images according to a plurality of bit planes, wherein the bit planes corresponding to different reconstructed images are not identical, and the bit number of each reconstructed image is N, and N is a positive integer smaller than M;fusing multi-frame reconstructed images to obtain a fused image of the original image. As the multi-frame reconstructed images directly come from the same frame image, thus ensuring the consistency of the image scene, it can be directly applied to exposure fusion without image registration, and the resulting fusion image will not contain ghost images. Compared with the prior art, the invention can avoid image blurring conveniently, highlight darkness and highlighted details at the same time, on the other hand, can reduce the algorithm resource overhead of image fusion.

A method and an apparatus for image filtering are described. Structural information is employed during the calculation of filtering coefficients. The structural information is described by the regions defined through an edge map of the image. In one embodiment, the region correlation between the target pixel and a contributing pixel is selected as a structural filtering coefficient. The region correlation, which indicates the possibility of two pixels being in the same regions, is calculated by evaluating the strongest edge cut by a path between the target pixel and a contributing pixel. The structural filtering coefficient is further combined with spatial information and intensity information to form a spatial-intensity-region (SIR) filter. The structural information based filter is applicable to applications such as denoising, tone mapping, and exposure fusion.

The invention discloses a low-light-level image enhancement method based on an MSR theory and exposure fusion, and solves the problems of damage to the overall structure of an image, excessive enhancement and the like in low-light-level image enhancement. The method comprises the steps of inputting an original image and extracting a V component of the original image; processing the V component byusing a local detail processing operator to obtain a detail processing graph; processing the V component by using an integral structure preserving operator to obtain a structure processing graph; defining the V component of the original image as a correction processing image; combining the three processing images by adopting an exposure fusion method to obtain an enhanced result image; and transferring from the HSV space to the RGB space for display to obtain an enhanced result graph. According to the invention, the regional detail richness based on the information entropy is used for accurately measuring the detail richness of the image, three different Gaussian kernel weights are adaptively calculated according to the regional detail richness, and three processing images are merged by combining an exposure fusion method. According to the method, image detail enhancement and structure and brightness maintenance are considered while the low-light-level image is enhanced. The method canbe applied to the fields of remote sensing, military, industry and medicine.