A method for adaptive reproduction and display of high dynamic range images

Abstract

The invention discloses a high dynamic range image adaptive reproduction display method. The method comprises the steps that a high dynamic range image is read so as to obtain the grayscale or brightness channel of the image; local mapping transformation is performed on the grayscale or brightness channel of the image by using a nonlinear tone mapping window model; local contrast measure calculation is performed based on a PLIP model; adaptive optimization double guidance image mapping constraints are designed to guide an objective optimization function to obtain the optimal result; and the result image is outputted. The high dynamic range image can be effectively displayed, the image edge and image detail information can also be maintained and the halo effect can be suppressed so as to have great adaptive capability and robustness, and the processing effect proves that the method has high practicality.

Description

technical field [0001] The invention relates to the field of image processing, and more specifically, to an adaptive reproduction and display method of high dynamic range images. Background technique [0002] For the photosensitive device of an imaging device, the dynamic range refers to the range between the gray scale or brightness value contained in the image from "darkest" to "brightest". The dynamic range of the image controls the extremely dark areas and The ability to show the details of extremely bright areas in one image at the same time. The range of most image data is generally 2 orders of magnitude or 8 bits, that is, the pixel gray value is between 0-255, and the human visual system can perceive scene brightness in a range of about 5 orders of magnitude. High dynamic range images can generally store larger orders of magnitude or more bytes of data, such as 10 bits or 16 bits, which can span a very wide range of pixel grayscale or brightness levels, and can bett...

AI Technical Summary

Problems solved by technology

Although the global mapping technology is relatively simple and can better maintain the overall contrast effect of the image, this method does not take into account the spatial position of the image pixels or the neighborhood related information between them, and the pixels are equally mapped in the image. As a result, the image contrast is greatly compressed, and the detailed information of the image is seriously lost.

Especially when dealing with complex scenes, it does not reflect the real human visual system response well

Images