Hybrid Algorithm Based on Hyper Spectral Noise Removal for Satellite Image

FLIC: Fast & Lossless Image Compression Algorithm for Hyper-Spectral Images

A Noise Removal Algorithm of Color Image

An algorithm of the color image noise removal algorithm is put forward based on the pixel operations. The idea of the algorithm is to read every pixel in a set order and determine whether the pixel level is consistent with the probability density function of impulse noise or not. If it is similar to noise pixel, the number of impulse noise in a certain mask is counted. If the number is less tha...

Hyper-Spectral Image Compression

Hyper-spectral images consist of huge amount of data. This paper presents a compression technique developed specifically for these images. This technique explores unique characteristics of the hyper-spectral images and incorporates them into the compression. It also exploits the wavelet transformation and bit plane entropy coding used in general image compression. In this technique, predicting ...

Geological noise removal in geophysical magnetic survey to detect unexploded ordnance based on image filtering

This paper describes the application of three straightforward image-based filtering methods to remove the geological noise effect which masks unexploded ordnances (UXOs) magnetic signals in geophysical surveys. Three image filters comprising of mean, median and Wiener are used to enhance the location of probable UXOs when they are embedded in a dominant background geological noise. The study ar...

Pbbo: a New Hybrid Algorithm for Satellite Image Classification

From last two decades many optimization techniques have been evolved. PSO and BBO are the two techniques that have been widely used in Swarm Optimization. PSO is better than many genetic algorithms. PSO has applications in various areas like Optimization, Neural Networks training, Fuzzy controls and etc. BBO is based on science of biogeography. BBO has some features common to PSO and Genetic al...