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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.