High-precision rapid focus detection method based on push-broom underwater hyperspectral original image

Abstract

The invention relates to a high-precision rapid focus detection method based on a push-broom underwater hyperspectral original image. The method comprises the following steps: collecting the push-broom underwater hyperspectral original image; carrying out bilinear interpolation down-sampling to obtain a sampling graph; performing noise suppression on the sampling image; carrying out overlapped Laplacian operator weighting, and calculating a central pixel point gray value of each image sub-block; summing gray values, and identifying an optimal coarse focusing position; focusing a stepping motor, and collecting a push-broom underwater hyperspectral original image; carrying out edge maintenance; decomposing the filtered image by adopting frequency domain wavelet transform, and recombining the filtered image; obtaining a fine focusing evaluation value of the push-broom underwater hyperspectral original image; and completing focusing identification. The obtained image focusing evaluation value has good real-time performance, unimodality, environmental applicability and noise resistance, and the fine focusing identification algorithm has better function sensitivity than the coarse focusing identification algorithm.

Description

technical field [0001] The invention belongs to the technical field of underwater hyperspectral detection, and relates to a focus detection method of a push-broom hyperspectral camera. Background technique [0002] The underwater imaging system can search, reconnaissance and monitor underwater targets, and can provide landform and topographic maps for the detection and exploitation of submarine oil and natural gas. In the maritime information acquisition technology, hyperspectral imaging technology, as a technology that can not only obtain hundreds of continuous band information at the same spatial position, but also can describe the target color, texture, and obtain the temporal and spatial distribution of the target, has significant advantages. Other imaging technologies have higher spectral resolution and provide a larger amount of information. They can not only reflect the physical and chemical characteristics of the observed object, but also construct the shape image of...

AI Technical Summary

Problems solved by technology

[0003] Traditional hyperspectral camera focusing is based on the experience of the focusing personnel. By manually adjusting the working distance of the camera, the human eye judges the focusing quality of the current hyperspectral image until the focusing personnel thinks that the current distance is the best distance. The focusing method is subject to human experience and level. Due to the influence of various factors, it is easy to make wrong judgments on high-precision hyperspectral images that are difficult to distinguish with the naked eye, and the focusing efficiency is not high

[0004] Later, the hyperspectral camera focusing method developed into a photoelectric autocollimation focusing method and an image processing-based focusing method. The accuracy of the photoelectric autocollimation focusing method is affected by factors such as light source intensity, air pressure, and temperature, and the focusing effect is unstable.

The existing focusing method based on the widely used gray-scale co-occurrence matrix-contrast (CON) based on image processing is established based on the gray-scale co-occurrence matrix-contrast (CON) in four directions of each central pixel point, although it can be reflected in The amount of local changes in the image, the clarity of the image and the depth of the grooves of the image texture, but the real-time performance of this method is not enough to meet the actual focusing needs; the mountain climbing search algorithm based on image processing, although the automatic focus search algorithm Algorithms are widely used in China, but they can only provide relative indicators of image clarity. The evaluation of image clarity is easily disturbed by factors such as noise, and local peak points are likely to appear in the focusing results. It is not suitable for underwater inspections that require high focus accuracy. focal use

The existing focusing method based on multiple images combined with image processing also lacks the depth of focus of the camera, the loss of edge information and structural information of the image by the noise removal algorithm, and the attenuation, selective absorption, and scattering of light by the water medium. As a result, the focal plane position of underwater imaging is more sensitive than that on land, and more careful considerations make the existing focusing aspects unable to meet the requirements of underwater image focusing, and the accuracy and precision of focusing need to be improved

The existing focusing method based on push-broom hyperspectral camera combined with image processing: the focusing method based on low-frequency and high-frequency amplitude and phase information constructed by quaternion wavelet transform is also limited to the identification of black and white stripe calibration plate images , Insufficient applicability to focusing images of underwater real scenes and complex land scenes, and the focusing efficiency is relatively low

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