Infrared image stripe noise elimination method

Abstract

The invention discloses an infrared image stripe noise elimination method. The method comprises the following steps: I. collecting an infrared image; II. calculating the average of N rows for the nth frame infrared image zn; III. calling a stripe noise estimation module by an image processor and estimating the stripe noise bn of the nth infrared image zn according to the average of N rows for the nth frame infrared image zn; and IV. subtracting the stripe noise bn of the nth infrared image zn from the nth infrared image through an image processor, thus eliminating the stripe noise in the nth frame infrared image zn. According to the method, the design is novel and reasonable, the steps are simple, and realization is convenient, the stripe noise in the infrared image can be processed in real time, and the method is strong in practicability, good in usage effect, and convenient to popularize and use.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a method for eliminating streak noise of an infrared image. Background technique [0002] Due to manufacturing process problems, the output circuit of the infrared focal plane array usually shares the same output circuit with the same column (or row) of pixels. Since the bias voltage of the column output circuit is not completely consistent, the generated image contains column stripes as the main feature. The non-uniform noise is called streak noise. [0003] In the prior art, methods for eliminating non-uniform noise mainly fall into two categories: calibration-based methods and scene correction-based methods. However, the calibration-based method cannot update the parameters in real time, and needs to assume that the parameters remain unchanged for a long period of time between two consecutive calibrations, while the bias voltage of the column output circu...

AI Technical Summary

Problems solved by technology

However, the calibration-based method cannot update the parameters in real time, and needs to assume that the parameters remain unchanged for a long period of time between two consecutive calibrations, while the column output circuit bias voltage changes quickly, so it cannot effectively eliminate noise

Although the scene-based correction method can update the parameters in real time, it also brings two problems: 1) the method needs a long time image sequence algorithm to converge; 2) using a long image sequence may cause "artifact" phenomenon (that is, displaying the previous image on the following image), it is also unable to effectively eliminate noise

Images