Multi-exposure image fusion method and system and storable medium

Abstract

The invention discloses a multi-exposure image fusion method and system and a storable medium, and belongs to the technical field of image processing, and the method comprises the steps: inputting an image, calculating a good exposure estimation weight and a chroma weight, and carrying out the convolution of a Gaussian pyramid of a comprehensive weight map and a Laplacian pyramid of the input image, and obtaining an initial fusion pyramid; secondly, carrying out local detail enhancement on the obtained brightest and darkest regions of interest by utilizing a fast local Laplacian filter (FLLF), then taking the maximum value of Laplacian coefficients to obtain a maximum coefficient Laplacian pyramid, updating the coefficients in the regions of interest into an initial fusion pyramid, and obtaining a maximum coefficient Laplacian pyramid; according to the method, under the condition that it is guaranteed that information is not lost in the brightest and darkest areas, proper enhancement can be carried out, the naturalness of light and shadow transition is guaranteed, and image details are clearer.

Description

technical field [0001] The present invention relates to the technical field of image processing, and more particularly to a multi-exposure image fusion method, system and storage medium. Background technique [0002] With the rapid development of ultra-high-definition digital industry and digital photography technology, people's pursuit of ultra-high-definition cool visual experience is more urgent. At present, the methods of multi-exposure image fusion mainly include: high dynamic range imaging (HDR), exposure image fusion algorithm and multi-exposure fusion method based on deep learning. Among them, the high dynamic range imaging method overcomes the defect of loss of details in the brighter and darker areas in the overexposure and underexposure images. This method takes several images of the same scene with different exposures and reconstructs them into HDR images. HDR imaging generally consists of two main steps: HDR reconstruction and tone mapping. First, take multipl...

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Problems solved by technology

[0006] In view of this, the present invention provides a multi-exposure fusion method, system and storage medium, based on weighted average adaptive factor and local detail enhancement, to solve the problems in the prior art that the overall brightness of the input image sequence is not well adjusted. Adaptation problems, lack of spatial neighborhood information, excessive detail increase, etc.

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