Classification of Hyperspectral Image using SVM
Post-Processing for Shape Preserving Filter and PCA

Global Journal of Computer Science and Technology,2020

This paper is based on experimentation to preserve shapes of the natural classes in a hyperspectral image post-classification of the image using SVM. The classifier classifies the vegetation types present in the hyperspectral image and then estimates the crop types present in the image. The result has been found very effective in characterizing significant spectral and spatial structures of objects in a scene.

Dark Channel Processing for Medical
Image Enhancement

IEEE 5th International WIE Conference,2019

The images obtained through biomedical instruments are not always satisfactory. They are often blurred or vague. This project concentrated on image processing system which enhances these biomedical images. Satisfactory results were obtained which showed clearer biomedical images. Further SSIM values and correlation factor are calculated to compare the results. The results were tested for different images obtained by medical instruments.

Dehazing of Aerial Images using Dark Channel
and Gamma Correction

An effective method to improve the contrast of hazed images by computing its dark channel image, calculating the atmospheric light, recovering the scene radiance and refining it by gamma correction. On testing the algorithm on real aerial images, we obtain significant results. This method is applicable to colored and gray-scale images. The experimental results show the SSIM index values and correlation factor nearly equal to one, after executing the algorithm on hazed images.

Self-Parking Car prototype

The prototype focuses on self-driving with parking in an environment created by Raspberry pi. The car is planned to be made smarter by data handling and machine learning. The results showed how self-parking can be implemented on regular cars and an ample amount of time and money can be saved by parallel parking systems.