Abstract
In the uncooled infrared imaging systems, owing to the non-uniformity of the amplifier in the readout circuit, the infrared image has obvious stripe noise, which greatly affects its quality. In this study, the generation mechanism of stripe noise is analyzed, and a new stripe correction algorithm based on wavelet analysis and gradient equalization is proposed, according to the single-direction distribution of the fixed image noise of infrared focal plane array. The raw infrared image is transformed by a wavelet transform, and the cumulative histogram of the vertical component is convolved by a Gaussian operator with a one-dimensional matrix, in order to achieve gradient equalization in the horizontal direction. In addition, the stripe noise is further separated from the edge texture by a guided filter. The algorithm is verified by simulating noised image and real infrared image, and the comparison experiment and qualitative and quantitative analysis with the current advanced algorithm show that the correction result of the algorithm in this paper is not only mild in visual effect, but also that the structural similarity (SSIM) and peak signal-to-noise ratio (PSNR) indexes can get the best result. It is shown that this algorithm can effectively remove stripe noise without losing details, and the correction performance of this method is better than the most advanced method.
Highlights
Infrared imaging has been widely used in military, agricultural, and medical applications.owing to the defects of focal plane array materials and manufacturing limitations [1], the response of the infrared focal plane array unit is inconsistent, and serious spatial fixed pattern noise (FPN) is generated in the infrared image [2]
The correction results based on total variation algorithm (TV) algorithm can protect the details and edge information of the image to the maximum extent, but many obvious vertical strips are still visible in the image
The results obtained by midway histogram equalization algorithm (MHE) algorithm can better remove vertical strips but will over-smooth important details in infrared images
Summary
Infrared imaging has been widely used in military, agricultural, and medical applications.owing to the defects of focal plane array materials and manufacturing limitations [1], the response of the infrared focal plane array unit is inconsistent, and serious spatial fixed pattern noise (FPN) is generated in the infrared image [2]. People usually use traditional methods to correct FPN noise, in addition to FPN, random noise is a part of the noise of the infrared image, and its energy is usually smaller than FPN. After the system is subjected to traditional non-uniformity correction, the FPN will be reduced, and random noise will become the main noise [3]. For uncooled infrared focal plane array (FPA), the FPA usually consists of a detector array, readout circuit and an analog-to-digital converter as shown, where the non-uniformity of the readout circuit will generate column FPN. The column FPN will appear as obvious vertical strips in a raw infrared image, as shown in Figure 1b [4]. To improve the quality of infrared images, stripe non-uniformity correction is required
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