A new approach for colored satellite image enhancement

Abstract

A unique method of image filtering has been developed that enhances the detail and sharpens the edges of colored satellite images. Histogram equalization coupled with a two stage data filtering process that applies convolution with laplacian and sharpening with laplacaian through the 3 color bands that produce the colored satellite images has yielded sharper clearer images. The initial enhancement using histogram equalization was followed by the first stage of a filtering process convolution with laplacian which highlighted the edges of the image. The application of the second stage filtering sharpening with laplacian yielded enhanced color reproduction and a more accurate depiction of information at sea and land levels than was available in the original image. An analysis of the statistical index and signal to noise ratio of the true color and false color of histogram equalization, convolution with laplacian and sharpening images showed the image. An analysis of the false color of histogram equalization, convolution with laplacian and sharpening images showed the image to be superior, in this study the multi spectral content in the satellite image was transformed into a composite colour image, and then convoluted using the laplacian technique. This study placed an emphasis on improving the detail and edge clarity of satellite images.

Hardware Acceleration of Histogram Equalization and Image Sharpening Filter on NIOSII Processor Based SOC on FPGA

“…Image enhancement also increases the difference between the object and the background. Thus, knowing the purpose of the image is important because making the right decision for which techniques to use is required [2]. The techniques in this research are based on the past research [2,3] which can be defined as the function below [1,11], respectively.…”

A unified histogram and laplacian based for image sharpening

“…Image enhancement also increases the difference between the object and the background. Thus, knowing the purpose of the image is important because making the right decision for which techniques to use is required [1]. The techniques in this research are based on the past research [1,2] which can be defined as the function below [10], respectively.…”

“…The processed image was done by sharpening, reducing noise by edge detecting, computing the statistic values, the resolution, and image sharpness respectively [6,7]. This continual research emphasizes on image enhancement of all kinds [1]. The objectives are to make comparisons of image sharpness from different type of input devices and develop the algorithms for image processing as well as noise detecting.…”

A novel nonlinear algorithm for typhoon cloud image enhancement

“…In [2], satellite image enhancement and smoothing towards automatic feature extraction is accomplished through an effective serial application of anisotropic diffusion processing and alternating sequential filtering. Attachoo and Pattanasethanon [3] proposed a method to enhance the detail and sharpen the edge of colored satellite cloud images. This method is similar to the wavelet decomposition, which divides the image into two layers, each layer is processed alone, and finally reconstructed.…”