Multi-exposure image ghosting-free fusion method under global gradient based on patch alignment

Abstract

The invention discloses a multi-exposure image ghosting-free fusion method under global gradient based on patch alignment, which comprises the following steps: reading a reference image, measuring the similarity between the reference image and an LDR image based on a multi-source bidirectional similarity measurement algorithm MBDS, and aligning a motion area in the LDR image by adopting a patch acceleration method; adopting a reconstruction algorithm to obtain an LDR image sequence aligned with the reference image; designing a pixel relative intensity weight formula and a global gradient weight formula; and carrying out weighted averaging on the two weight expressions to obtain a final weight expression, inputting the weight map and the LDR image sequence in the Laplacian pyramid to carry out image fusion, and outputting a fused image. According to the method, the problem of artifacts occurring under dynamic scene fusion is effectively solved, the LDR image is registered based on the reference image, the fusion time is saved, the robustness is higher, then multi-scale decomposition fusion is carried out in the Laplacian pyramid, the fusion effect is better, and the obtained HDR image is rich in detail information and better in visual effect.

Description

technical field [0001] The invention relates to the technical field of image fusion, in particular to a multi-exposure image ghost-free fusion method under the global gradient based on patch alignment. Background technique [0002] With the development of image equipment and digital image processing technology, the reproduction of real scenes has become the most urgent demand of human beings. Real scenes can display a wide dynamic range, and the human eye can also adapt to real scenes with a wide dynamic range, but ordinary image acquisition devices and display devices cannot capture and display high dynamic range scenes. Therefore, high dynamic range image (High Dynamic Range Image, HDRI) processing provides a new way to reproduce the real scene, and has become a research hotspot. Obtaining HDR images through a set of multi-exposure image fusion is a commonly used acquisition method. However, when there are moving objects in the real scene, such as moving cars, pedestrians...

AI Technical Summary

Problems solved by technology

The most successful algorithms use optical flow (OF) to register images, but these methods still suffer from ghosting in the presence of large motion or complex occlusions or aliasing

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