An Algorithm for Salt and Pepper Noise Removal Based on Information Entropy

Zhao, Feng; Chuan, Rui; Jia, Qing Xuan

doi:10.4028/www.scientific.net/amm.220-223.2273

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…This deterioration is classified as salt and pepper noise (SPN) and random valued impulse noise [11,12]. SPN degrades the image quality to a great extent [13]. Therefore, many linear/nonlinear filters have been developed to solve the problem.…”

Section: Introductionmentioning

confidence: 99%

A new method based on pixel density in salt and pepper noise removal

Erkan¹,

Gökrem²

2018

Turk J Elec Eng & Comp Sci

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Abstract:In this paper, we deliver a new method to remove salt and pepper noise, which we refer to as based on pixel density filter (BPDF). The first step of the method is to determine whether or not a pixel is noisy, and then we decide on an adaptive window size that accepts the noisy pixel as the center. The most repetitive noiseless pixel value within the window is set as the new pixel value. By using 18 test images, we give the results of peak signal-to-noise ratio (PSNR), structural similarity (SSIM), image enhancement factor (IEF), standard median filter (SMF), adaptive median filter (AMF), adaptive fuzzy filter (AFM), progressive switching median filer (PSMF), decision-based algorithm (DBA), modified decision-based unsymmetrical trimmed median filter (MDBUTMF), noise adaptive fuzzy switching median filter (NAFSM), and BPDF. The results show that BPDF produces better results than the above-mentioned methods at low and medium noise density.

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Section: Introductionmentioning

confidence: 99%

A new method based on pixel density in salt and pepper noise removal

Erkan¹,

Gökrem²

2018

Turk J Elec Eng & Comp Sci

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“…This deterioration is categorized as salt and pepper noise (SPN) [13,14]. SPN generally reduces the image quality [15]. Consequently, many linear/nonlinear filters have been developed to sort out this problem.…”

Section: Related Workmentioning

confidence: 99%

Implementation and Optimization of Image Processing on the Map of SABRE i.MX_6

2021

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Vision relieves humans to understand the environmental deviations over a period. These deviations are seen by capturing the images. The digital image plays a dynamic role in everyday life. One of the processes of optimizing the details of an image whilst removing the random noise is image denoising. It is a well-explored research topic in the field of image processing. In the past, the progress made in image denoising has advanced from the improved modeling of digital images. Hence, the major challenges of the image process denoising algorithm is to advance the visual appearance whilst preserving the other details of the real image. Significant research today focuses on wavelet-based denoising methods. This research paper presents a new approach to understand the Sobel imaging process algorithm on the Linux platform and develop an effective algorithm by using different optimization techniques on SABRE i.MX_6. Our work concentrated more on the image process algorithm optimization. By using the OpenCV environment, this paper is intended to simulate a Salt and Pepper noisy phenomenon and remove the noisy pixels by using Median Filter Algorithm. The Sobel convolution method included and used in the design of a Sobel Filter and then process the image following the median filter, to achieve an effective edge detection result. Finally, this paper optimizes the algorithm on SABRE i.MX_6 Linux environment. By using algorithmic optimization (lower complexity algorithm in the mathematical sense, using appropriate data structures), optimization for RISC (loop unrolling) processors, including optimization for efficient use of hardware resources (access to data, cache management and multi-thread), this paper analyzed the different response parameters of the system with varied inputs, different compiler options (O1, O2, or O3), and different doping degrees. The proposed denoising algorithm shows the meaningful addition of the visual quality of the images and the algorithmic optimization assessment.

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A Comparative Review for Color Image Denoising

Ashpreet

2023

Advances in Multimedia and Interactive Technologies

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With the explosion in the number of color digital images taken every day, the demand for more accurate and visually pleasing images is increasing. Images that have only one component in each pixel are called scalar images. Correspondingly, when each pixel consists of three separate components from three different signal channels, these are called color images. Image denoising, which aims to reconstruct a high-quality image from its degraded observation, is a classical yet still very active topic in the area of low-level computer vision. Impulse noise is one of the most severe noises which usually affect the images during signal acquisition stage or due to the bit error in the transmission. The use of color images is increasing in many color image processing applications. Restoration of images corrupted by noises is a very common problem in color image processing. Therefore, work is required to reduce noise without losing the color image features.

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An Algorithm for Salt and Pepper Noise Removal Based on Information Entropy

Cited by 3 publications

References 16 publications

A new method based on pixel density in salt and pepper noise removal

A new method based on pixel density in salt and pepper noise removal

Implementation and Optimization of Image Processing on the Map of SABRE i.MX_6

A Comparative Review for Color Image Denoising

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