|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|4970363||1450118||2018||9 صفحه PDF||سفارش دهید||دانلود کنید|
- We propose a multi-scale filtering strategy to better remove the strip noise.
- Wavelet decomposition is used to separate original image into three scale levels.
- A novel 1D guided filter is used to further extract strips from textures.
In uncooled long-wave infrared (LWIR) imaging systems, non-uniformity of the amplifier in readout circuit will generate significant noise in captured infrared images. This type of noise, if not eliminated, may manifest as vertical and horizontal strips in the raw image and human observers are particularly sensitive to these types of image artifacts. In this paper we propose an effective non-uniformity correction (NUC) method to remove strip noise without loss of fine image details. This multi-scale destriping method consists of two consecutive steps. Firstly, wavelet-based image decomposition is applied to separate the original input image into three individual scale levels: large, median and small scales. In each scale level, the extracted vertical image component contains strip noise and vertical-orientated image textures. Secondly, a novel multi-scale 1D guided filter is proposed to further separate strip noise from image textures in each individual scale level. More specifically, in the small scale level, we choose a small filtering window for guided filter to eliminate strip noise. On the contrary, a large filtering window is used to better preserve image details from blurring in large scale level. Our proposed algorithm is systematically evaluated using real-captured infrared images and the quantitative comparison results with the state-of-the-art destriping algorithms demonstrate that our proposed method can better remove the strip noise without blurring image fine details.
Journal: Signal Processing: Image Communication - Volume 60, February 2018, Pages 13-21