A local adaptive threshold noise detection linear interpolation filter (LALIF) for stripe noise removal in infrared images

2016 ◽  
Author(s):  
Jihong Pei ◽  
Mi Zou ◽  
Lixia Wang
Keyword(s):  
Linear Interpolation ◽  
Noise Removal ◽  
Adaptive Threshold ◽  
Noise Detection ◽  
Infrared Images ◽  
Interpolation Filter ◽  
Local Adaptive Threshold

Decision Based Median Filter algorithm using Resource Optimized FPGA to Extract Impulse Noise

2014 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Rutuja Nandkumar Kulkarni ◽  
Pradip C Bhaskar
Keyword(s):  
Impulse Noise ◽  
Median Filter ◽  
Noise Removal ◽  
Mean Value ◽  
Linear Filter ◽  
Noise Detection ◽  
Object Boundary ◽  
Typical Application ◽  
Impulse Noise Removal ◽  
Noisy Pixel

Median filter is a non-linear filter used in image processing for impulse noise removal. It finds its typical application in the situations where edges are to be preserved for higher level operations like segmentation, object recognition etc. This paper presents an accurate and efficient noise detection and filtering algorithm for impulse noise removal. The algorithm includes two stages: noise detection followed by noise filtering. The proposed algorithm replaces the noisy pixel by using  median value when other pixel values, 0’s or 255’s are present in the selected window and when all the pixel values are 0’s and 255’s then the noise pixel is replaced by mean value of all the elements present in the selected window. Similarly algorithm checks for five different conditions to preserve image details, object boundary in high level of noise densities. This median filter was designed, simulated and synthesized on the Xilinx family of FPGAs (XC3S500E of Spartan-3E). The VHDL was used to design the above 2-D median filter using ISE (Xilinx) tool & tested & compared for different grayscale images.

scholarly journals Feature Point Extraction and Tracking Based on a Local Adaptive Threshold

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 44325-44334 ◽  
Author(s):  
Hang Li ◽  
Hongfan Yang ◽  
Kaiyang Chen
Keyword(s):  
Adaptive Threshold ◽  
Feature Point ◽  
Feature Point Extraction ◽  
Local Adaptive Threshold

Adaptive Partition-Cluster-Based Median Filter for Random-Valued Impulse Noise Removal

2018 ◽  
Vol 27 (07) ◽  
pp. 1850110
Author(s):  
Ke Pang ◽  
Zaifeng Shi ◽  
Jiangtao Xu ◽  
Suying Yao
Keyword(s):  
Impulse Noise ◽  
Parallel Implementation ◽  
Median Filter ◽  
Noise Removal ◽  
Noise Detection ◽  
Computation Complexity ◽  
Noise Filter ◽  
The Arts ◽  
Objective Quality ◽  
Significant Attention

As the most popular nonlinear denoise technique, the median filter has attracted significant attention in recent years. In this paper, a novel adaptive median filter is presented to remove random-valued impulse noise in images, named Adaptive Partition-Cluster-Based Median (APCM) Filter. Based on the partition cluster idea, the noise detector classifies pixels into different groups and identifies the noisy pixels in different regions adaptively without iterations. According to the results of noise detection, an improved adaptive decision-based filter is presented to restore the pixels which are corrupted by random-valued impulse noise. The proposed filter technique is open to any impulse noise. Extensive simulation results demonstrate that the proposed method substantially outperforms other state-of-the-arts impulse noise filter techniques both visually and in terms of objective quality measures. Furthermore, the proposed method is much friendly to the hardware parallel implementation of image processing because of its low computation complexity and simple realizable structure.

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