Abstract
In the field of agriculture, image processing plays a significant role in which Image compression and Encryption is the most important tool. Image processing provides applications for agriculture in detection of unwanted growth of crops and its health monitoring. Image Encryption and Compression techniques are utilized to achieve better reconstructed image. Generally, remote sensing equipment is utilized in broadcast of images that are captured in the agriculture field. During transmission, image size and bandwidth are the main issues which require huge storage space and large bandwidth for the transmission. Hence, it is obligatory to compress the image before transmission. Various compression and Encryption methodologies are used so far. But there are some limitations of the existing techniques like high encryption time and quality of reconstructed image will be affected. Therefore, to overwhelm these limitations Novel Homomorphic Encryption algorithm (NHE) for encryption process and an Enhanced Discrete Wavelet Transform (EDWT) for compression procedure (NHE-EDWT) is proposed. The Image is encrypted, compressed, decompressed, and finally decrypted to get the resultant image. The advantage of using this enhanced methodology diminishes the time taken for encryption and retains a better quality reconstructed image. Finally, the performances are measured for peak signal to noise ratio (PSNR), Execution Time, and Compression ratio. On comparing with the existing methodologies, this proposed work offers better efficiency in PSNR approximately 15.06% with classic methods, Compression ratio is improved about 84.02%, and Encryption time is decreased about 89.70%. The quality of reconstructed images improved, the size of the image is reduced by improving the compression ratio. Thus reduces the required bandwidth for image transmission. Decreased encryption time reduces the time consumption for computation.
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Kulalvaimozhi, V.P., Alex, M.G. & Peter, S.J. A Novel Homomorphic Encryption and an enhanced DWT (NHE-EDWT) compression of crop images in agriculture field. Multidim Syst Sign Process 31, 367–383 (2020). https://doi.org/10.1007/s11045-019-00660-9
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DOI: https://doi.org/10.1007/s11045-019-00660-9