Open AccessConversion of Landsat 8 multispectral data through modified private content‐based image retrieval technique for secure transmission and privacy
Author(s) -
Shakya Amit K.,
Ramola Ayushman,
Vidyarthi Anurag
Publication year - 2020
Publication title -
engineering reports
Language(s) - English
Resource type - Journals
ISSN - 2577-8196
DOI - 10.1002/eng2.12273
Subject(s) - encryption , multispectral image , computer science , pixel , artificial intelligence , histogram , computer vision , similarity (geometry) , image retrieval , image (mathematics) , feature (linguistics) , pattern recognition (psychology) , linguistics , philosophy , operating system
In this research work, we have developed a new image encryption‐based algorithm for Landsat 8 satellite images. Image statistical parameters related to first‐order image statistics, that is, mean (μ), SD ( σ) , and variance ( σ 2 ) are used to obtain the feature values for both original images and their encrypted versions. Multispectral satellite images generally contain a wide range of bands, which is 9 to 11 specifically for the Landsat 8 satellite. Hence, the information content of these images is richer than typical images. Through this algorithm, we aim to reduce the image content by randomly selecting only 10% of the total image pixels. These pixels are used to create new images, the so‐called encrypted images. The visual presentation of the encrypted image resembles a noisy picture. First‐order image statistics are calculated for both original images and their encrypted counterparts. These parameters show a similarity in their numerical values for both original and encrypted images. Thus, noisy pictures can be used for transmission in place of the original image when an outcome is decided through statistical image features. The visual similarity in the original images and encrypted images is obtained from the histogram signature plot for both original and encrypted images. The proposed algorithm can hence be used to convert image data for secure transmission and privacy.