Demosaicing and compression fusion frame for MSFA hyperspectral image

Abstract

The invention discloses a demosaicing and compression fusion frame for an MSFA hyperspectral image. The demosaicing and compression fusion frame comprises a PPI image generation module, a compression and decompression module and a rapid demosaicing module. The PPI image generation module obtains various features in the Raw image by using a DPG-Net network, carries out image reconstruction according to the features, outputs the reconstructed image and generates a PPI image; the compression and decompression module is used for compressing and decompressing the Raw graph and the PPI graph and reducing the size of a compressed file and the complexity of an algorithm; the rapid demosaicing module firstly separates spectrum channels of the Raw graph and the PPI graph; subtracting the separated Raw graph from the PPI graph; and carrying out convolution on the difference between the two images, and adding the image after convolution with the PPI to obtain a final demosaiced image. The frame provided by the invention has the characteristics of high compression rate and high demosaicing speed at the decompression end.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a hyperspectral image demosaicing and compression fusion framework. Background technique [0002] As a new imaging system, hyperspectral imaging has been widely used in many fields such as land surveying and mapping, urban and rural construction, statistical investigation, agricultural and forestry resource monitoring, and true and false target recognition with the continuous maturity of imaging technology. Hyperspectral imaging techniques can be roughly divided into two types: one, generate a separate image for each spectrum; two, use MSFA to make one image contain multiple channel information. The former has slower imaging speed, more expensive cameras and cannot accurately capture moving objects due to the need to replace filters and other operations; while the latter only has a single spectral channel information (color) at each pixel, such as figure 1 A...

AI Technical Summary

Problems solved by technology

The former has slower imaging speed, more expensive cameras, and cannot accurately capture moving objects due to the need to replace filters and other operations; while the latter only has a single spectral channel information (color) at each pixel, such as figure 1 As shown, when the ligh...

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