Infrared stripe correction algorithm based on wavelet decomposition and total variation-guided filtering

Ende Wang,Ping Jiang,Xuepeng Li,Hui Cao

doi:10.1186/s41476-019-0123-2

Abstract

Stripe non-uniformity severely affects the quality of infrared images. It is challenging to remove stripe noise in low-texture images without blurring the details. We propose a single-frame image stripe correction algorithm that removes infrared noise while preserving image details. Firstly, wavelet transform is used for multi-scale analysis of the image. At the same time, Total variation model is used for small window to smooth the original image. The small-scale total variation model can well preserve the edge information of the image, but it will leave stripe noise. Therefore, according to the prior knowledge of the vertical component of the stripe noise, the spatial filtering is finally performed: the smoothed image is used as the guide image for the stripe noise denoising. It is possible to prevent the lead filter from mistaking the strong stripe noise as edge detail, resulting in corrected image residual streak noise. The algorithm is systematically evaluated by experiments on simulated images and original infrared images, as well as compared with the current advanced infrared stripe non-uniformity correction algorithms. It is proved that our algorithm can better eliminate stripe noise and preserve edge details.

Highlights

Infrared imaging technology has a wide range of applications in the industrial, military, and medical fields
The resulting infrared images suffer from severe spatial domain fixed pattern noise (FPN) that reduces their quality [2, 3]
The considerations of wavelet transform、total variation smoothing and guiding filter are described in detail, and the implementation process of the whole algorithm is taken as a reference

Summary

Introduction

Infrared imaging technology has a wide range of applications in the industrial, military, and medical fields. The so-called infrared focal plane array (IRFPA) constitutes the core of infrared imaging systems, and possesses advantageous characteristics such as small size, low production cost, and high sensitivity [1]. IRFPA typically consist of a detector array and readout circuitry. Owing to component mismatch and changes in parameters during the manufacturing process, the pixel spatial response and the bias voltage of the readout circuitry are different. The resulting infrared images suffer from severe spatial domain fixed pattern noise (FPN) that reduces their quality [2, 3]. Stripe non-uniformity is a special FPN caused by the non-uniformity of the amplifier in the readout circuitry

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