Multi-exposure image fusion method

An image fusion and multi-exposure technology, which is applied in the field of image processing, can solve the problems of incomplete ghost removal and incomplete detail information retention, and achieve the effect of clear image details

Active Publication Date: 2019-05-14
SOUTHWEST COMP
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  • Abstract
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Problems solved by technology

[0006] The technical problem to be solved by the present invention is the technical problem of ...

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Embodiment 1

[0078] This embodiment provides a multi-exposure image fusion method, such as figure 1 , the multi-exposure image fusion method includes:

[0079] Step 1, using the exposure luminance and chrominance information of the LDR image sequence to construct an initial weight map;

[0080]

[0081] in, is the exposure brightness of the kth input image, is the chroma information of the kth input image, θ 1 for The exponential parameter of , θ 2 for The index parameter;

[0082] Step 2: Carry out moving object detection on the LDR image sequence to detect the moving area, use the superpixel segmentation ghost elimination method to eliminate the ghost, and complete the ghost correction for the initial weight map of the step 1;

[0083]

[0084] in, is the ghost elimination item, and the weight of the motion area is zero;

[0085] Step 3, normalize the weight map after ghost correction in step 3 to obtain:

[0086]

[0087] Among them, N is the number of input imag...

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Abstract

The invention relates to a multi-exposure image fusion method, which solves the technical problems of incomplete detail information retention and incomplete ghosting elimination, and comprises the following steps of: 1, constructing an initial weight map by using exposure brightness and chroma information of a multi-exposure image sequence; 2, firstly, moving object detection is conducted on the low-dynamic image sequence, a moving area is calculated, and then a ghosting eliminating method based on super-pixel segmentation is used for eliminating ghosting; 3, completing ghosting correction onthe initial weight map in the step 1; 4, performing normalization processing on the weight map after ghosting correction in the step 3; and 5, constructing a weighted Gaussian pyramid according to theweight graph in the step 4, constructing a Laplacian pyramid of a low-dynamic image sequence, defining detail gain items, calculating a fusion pyramid, and performing image reconstruction according to the fusion pyramid to obtain a fusion image HDR. The problem is well solved, and the method can be used for image processing.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a multi-exposure image fusion method. Background technique [0002] The dynamic representation range of ordinary digital cameras is far lower than that of natural scenes, and the captured images often have "too bright" or "too dark" areas, which cannot satisfy people's visual experience. High dynamic range (HDR) Imaging technology aims to solve this problem. Multi-exposure image fusion is an effective way to achieve high dynamic range display of images. Different from the tone-mapping-based HDR method, the multi-exposure image fusion-based method skips the step of acquiring HDR image data, so the time-consuming to achieve HDR imaging is usually less than the tone-mapping-based method. [0003] In recent years, many experts and scholars have conducted in-depth research on multi-exposure image correlation algorithms. For the first time, Mertens T. et al. proposed a mult...

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Application Information

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IPC IPC(8): G06T5/00G06T5/50
Inventor 瞿中黄旭刘妍
Owner SOUTHWEST COMP
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