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Research Paper | Computer Science & Engineering | India | Volume 9 Issue 9, September 2020 | Rating: 6.4 / 10
Efficient Image Encryption EIE - Compression System Using Haar Wavelets Using Matlab
Kavita [91] | Anil Vadhwa
Abstract: Recently, multimedia and network technologies field is developing rapidly. For that reason privacy and security becomes the leading challenging issues as the data is transmitted openly across the network and along with this, storage space is also an important issue which can’t be unseen. So encryption is used to provide the privacy and security to the multimedia, and similarly compression can be used to reduce the storage space. Size reduction also minimizes the transmission time. For securing images, several encryption techniques have been used. In this Report, an efficient image encryption-compression system is designed. The proposed image encryption scheme operated in the prediction error domain is shown to be able to provide a reasonably high level of security. A new image compression algorithm is also implemented using Haar Wavelet Transform which efficiently compresses the encrypted image. By Using Haar wavelet transform with ETC there is better compression efficiency. The approach applied in this Report is proved more efficient in terms of Compression Ratio (CR), Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR). For implementing the proposed algorithm, the Image Processing Toolbox under MATLAB software is used. Present day application requires various kinds of images and pictures as sources of information for interpretation and analysis. Whenever an image is converted from one form to another such as digitizing, scanning, transmitting, storing, etc. , some of the degradation may occur at the output. Hence the output image has to undergo a process called image enhancement which consists of a collection of techniques that seek to improve the visual appearance of the image. Image enhancement is basically improving the int
Keywords: Image fusion Pixel significance, Multi-focus Multi-sensor Bilateral filter, Cross bilateral filter, Detail image Detail strength
Edition: Volume 9 Issue 9, September 2020,
Pages: 1330 - 1335