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Open AccessJournal Article

Analysis the Impact of Filters in Spatial Domain on Grayscale Image

Jain Prince, +1 more
- 28 Dec 2011 - 
- Vol. 36, Iss: 7, pp 47-51
TLDR
The main objective of this paper is to remove noise from the gray scale images to better understand the contents of the original image by applying various filter algorithms to get the blurred free and noise free image.
Abstract
Computer graphics is the branch of computer science which deals with the study of graphics and images. Advancement in the technology brings the development in the image processing techniques, which deals with the image acquisition, image enhancement, restoration etc. Different type of noise got added up to the image while image acquisition leading to the final corrupted image. The main objective of this paper is to remove noise from the gray scale images to better understand the contents of the original image by applying various filter algorithms to get the blurred free and noise free image. For this an algorithm is developed and presented in shape of flowchart. This paper compares the different filters used for the noise removal from an image. It studies various filters for noise removal and finds the opinion that which is best for every type of image. As every image processing algorithms works differently for different image, there are different methods to deal with different types of noise.

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Citations
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Journal ArticleDOI

Image Enhancement Techniques: A Study

TL;DR: An overview of Image Enhancement Processing Techniques in Spatial Domain is presented, which categorise processing methods based representative techniques of Image enhancement into two categories: Spatial domain and Frequency Domain Enhancement.
Journal ArticleDOI

Qualitative and quantitative analysis of non-uniform dark images

TL;DR: Results showed that few parts where no information was being noticed before processing the digital image, now provides information to the subject after processing.
References
More filters
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Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization

TL;DR: This scheme can remove salt-and-pepper-noise with a noise level as high as 90% and show a significant improvement compared to those restored by using just nonlinear filters or regularization methods only.
Proceedings ArticleDOI

Removing salt-and-pepper noise from binary images of engineering drawings

TL;DR: A noise removal algorithm that can remove noise while retaining fine graphical elements is presented in this paper and the algorithm studies the neighborhood of thin lines before choosing to remove or retain it.
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Digital Image Processing using Local Segmentation

TL;DR: The new FUELS denoising algorithm is shown to be highly competitive with state-of-the-art algorithms on a range of images and the minimum message length information theoretic criterion for model selection (MML) is used to select between models having different structure and complexity.

Filtering Noise on two dimensional image Using Fuzzy Logic Technique

TL;DR: It is shown that FLT is a preferred method of rejecting impulse noise both in terms of computational complexity and lower residual NSR(noise to signal ratio).
Proceedings ArticleDOI

Empowering spatial domain filters of digital image processing with IFE tool

TL;DR: In this paper types of image noises are briefly described and a comparison of results of restored images obtained using IFE tool is made with MATLAB and Paint shop pro software.