A Method for Removing Streak Noise in Infrared Image Based on Local Correlation

Abstract

The invention belongs to the field of infrared image processing, and specifically discloses a method for removing stripe noise in infrared images based on local correlation, which includes: calculating the expected output value of the pre-corrected pixel point through one-dimensional horizontal mean filtering; calculating the expected output value of the pre-corrected pixel point. Expected output, use the correction parameter corresponding to the pixel above the pre-corrected pixel to correct the pre-corrected pixel to obtain the expected output; under the condition that the sum of squares of the difference between the expected output and the expected output is minimized, it is achieved through inter-column iteration Adaptive update of correction parameters; use new correction parameters to correct pre-corrected pixels; correct the next pixel in the same row until one frame of image correction is completed. The method of the present invention does not need to store a frame of image to calculate the statistical characteristics of the image. It only needs to cache the adjacent elements of the current pixel point, and combined with the local correlation between columns of stripe noise, stripe noise removal of a single frame image can be achieved, and more It is suitable for the characteristics of infrared image data pipeline.

Description

technical field [0001] The invention belongs to the field of infrared image processing, and more particularly relates to a method for removing stripe noise in infrared images based on local correlation. Background technique [0002] In the infrared imaging system, the infrared focal plane array usually shares the same output circuit with the pixels in the same column. Since the bias voltage of the row output circuit is not completely consistent, and the output circuit has non-uniformity, the image generated by the infrared imaging system will be uneven. Contains non-uniform noise characterized by streaks, called streak noise. Traditional scene-based non-uniform correction algorithms or calibration-based correction algorithms cannot effectively remove this streak noise. [0003] At present, the methods to solve the streak noise in infrared images are mainly divided into two categories: one is the removal algorithm based on statistical features, this type of algorithm often a...

AI Technical Summary

Problems solved by technology

This scheme can remove the streak noise in the infrared image without losing the original information of the image, but these algorithms have a large amount of calculation, which is not conducive to real-time hardware implementation

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