HYBRID IMAGE COMPRESSION TECHNIQUE USING DEEP LEARNING MODEL FOR ENHANCED RELIABILITY AND DATA TRANSMISSION

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Dr. K Bhanu Rekha , Dr. Safinaz S

Abstract

Image compression is the way of data compression which could be applicable to digital form of images for the purpose of reducing the cost of storage or transmission and any algorithm would consider visual perception or statistical properties of an image to establish enhanced results. The compression techniques might be lossy or lossless type. The supreme image quality at a particular compression rate is the major aim of any image compression approach.


Objective: In this current research, image compression is carried out with the support of hybrid Convolution Neural Network (CNN) and Random Forest (RF) approach.


Data description: The proposed methodology is executed in python environment and the performance metrics is evaluated and outcomes attained are compared with existing research works to verify the effectiveness of suggested concept. 

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