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A Comparative Study of Removal Noise from Remote Sensing Image

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TLDR
This paper attempts to undertake the study of three types of noise such as Salt and Pepper (SPN), Random variation Impulse Noise (RVIN), Speckle (SPKN) and they are compared with one another to choose the base method for removal of noise from remote sensing image.
Abstract
This paper attempts to undertake the study of three types of noise such as Salt and Pepper (SPN), Random variation Impulse Noise (RVIN), Speckle (SPKN). Different noise densities have been removed between 10% to 60% by using five types of filters as Mean Filter (MF), Adaptive Wiener Filter (AWF), Gaussian Filter (GF), Standard Median Filter (SMF) and Adaptive Median Filter (AMF). The same is applied to the Saturn remote sensing image and they are compared with one another. The comparative study is conducted with the help of Mean Square Errors (MSE) and PeakSignal to Noise Ratio (PSNR). So as to choose the base method for removal of noise from remote sensing image.

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Journal ArticleDOI

Sensor Correction of a 6-Band Multispectral Imaging Sensor for UAV Remote Sensing

Joshua Kelcey, +1 more
- 18 May 2012 - 
TL;DR: The proposed corrections improve the quality of the raw multispectral imagery, facilitating subsequent quantitative image analysis, and the identification of platform limitations and sensor idiosyncrasies.
Journal ArticleDOI

Some novel hybrid forecast methods based on picture fuzzy clustering for weather nowcasting from satellite image sequences

TL;DR: This paper proposes two novel hybrid forecast methods based on picture fuzzy clustering based on spatiotemporal regression for weather nowcasting which are equipped with advanced training processes which enhance the accuracy of predicted outputs.

A Comparative Study of Various Types of Image Noise and Efficient Noise Removal Techniques

Jahid Ali
TL;DR: The results of applying different noise types to an image model are presented and a comparative analysis of noise removal techniques is done and the results of various noise reduction techniques are investigated.
Journal ArticleDOI

Monitoring reservoir storage in South Asia from multisatellite remote sensing

TL;DR: In this paper, a suite of satellite observations were combined to achieve high-quality estimation of reservoir storage and storage variations in South Asia from 2000 to 2012, using water surface area estimations from the MODIS vegetation indices product and the area-elevation relationship to estimate reservoir storage.
Journal ArticleDOI

Assessment of pan-sharpening methods applied to image fusion of remotely sensed multi-band data

TL;DR: The Ehler method shows a better result for spatial details and color reproduction than GS, M-IHS, HPF and W-PCA, and it is found that all fusion methods reproduce both color and spatial information close to the original image.
References
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Book

Fundamentals of digital image processing

TL;DR: This chapter discusses two Dimensional Systems and Mathematical Preliminaries and their applications in Image Analysis and Computer Vision, as well as image reconstruction from Projections and image enhancement.
Book

Digital Image Processing Using MATLAB

TL;DR: 1. Fundamentals of Image Processing, 2. Intensity Transformations and Spatial Filtering, and 3. Frequency Domain Processing.
Journal ArticleDOI

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.
Journal ArticleDOI

Wavelet based image fusion techniques — An introduction, review and comparison

TL;DR: An introduction to wavelet transform theory and an overview of image fusion technique are given, and the results from a number of wavelet-based image fusion schemes are compared.
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