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具有嵌入式纠错机制的抗噪局部二值模式。

Noise-resistant local binary pattern with an embedded error-correction mechanism.

机构信息

BeingThere Centre, Institute of Media Innovation, Nanyang Technological University, Singapore.

出版信息

IEEE Trans Image Process. 2013 Oct;22(10):4049-60. doi: 10.1109/TIP.2013.2268976. Epub 2013 Jun 17.

Abstract

Local binary pattern (LBP) is sensitive to noise. Local ternary pattern (LTP) partially solves this problem. Both LBP and LTP, however, treat the corrupted image patterns as they are. In view of this, we propose a noise-resistant LBP (NRLBP) to preserve the image local structures in presence of noise. The small pixel difference is vulnerable to noise. Thus, we encode it as an uncertain state first, and then determine its value based on the other bits of the LBP code. It is widely accepted that most of the image local structures are represented by uniform codes and noise patterns most likely fall into the non-uniform codes. Therefore, we assign the value of an uncertain bit hence as to form possible uniform codes. Thus, we develop an error-correction mechanism to recover the distorted image patterns. In addition, we find that some image patterns such as lines are not captured in uniform codes. Those line patterns may appear less frequently than uniform codes, but they represent a set of important local primitives for pattern recognition. Thus, we propose an extended noise-resistant LBP (ENRLBP) to capture line patterns. The proposed NRLBP and ENRLBP are more resistant to noise compared with LBP, LTP, and many other variants. On various applications, the proposed NRLBP and ENRLBP demonstrate superior performance to LBP/LTP variants.

摘要

局部二值模式 (LBP) 对噪声敏感。局部三元模式 (LTP) 部分解决了这个问题。然而,LBP 和 LTP 都将损坏的图像模式视为原样。鉴于此,我们提出了一种抗噪局部二值模式 (NRLBP),以在存在噪声的情况下保留图像的局部结构。小的像素差异容易受到噪声的影响。因此,我们首先将其编码为不确定状态,然后根据 LBP 码的其他位来确定其值。人们普遍认为,大多数图像局部结构由均匀码表示,噪声模式很可能落入非均匀码中。因此,我们为不确定位分配值,以形成可能的均匀码。因此,我们开发了一种纠错机制来恢复失真的图像模式。此外,我们发现一些图像模式,如线条,无法用均匀码表示。这些线条模式可能比均匀码出现的频率低,但它们代表了一组用于模式识别的重要局部基元。因此,我们提出了一种扩展的抗噪局部二值模式 (ENRLBP) 来捕获线条模式。与 LBP、LTP 和许多其他变体相比,所提出的 NRLBP 和 ENRLBP 对噪声更具抵抗力。在各种应用中,所提出的 NRLBP 和 ENRLBP 表现出优于 LBP/LTP 变体的性能。

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