Satellite/Aerial Image Compression Using Adaptive Block Truncation Coding Technique

Balakrishnan, Binu; Darsana, Sobhana; Mathews, Jayamol; Nair, Madhu S.

doi:10.1007/s12524-018-0830-y

Cited by 9 publications

(2 citation statements)

References 11 publications

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“…BTC is first proposed by Delp and Mitchell in 1979 for data compression [40]. As a simple and fast lossy compression technique, BTC has been widely employed in many applications such as image compression, image watermarking, image retrieval, and so on [41][42][43][44]. It performs standard moments preserving quantization during image coding so that it can achieve both acceptable image quality and low storage space.…”

Section: Block Truncation Codingmentioning

confidence: 99%

Secure Outsourcing Algorithm of BTC Feature Extraction in Cloud Computing

Jiang

Yang

2020

IEEE Access

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Advances in cloud computing have aroused many researchers' interest in privacy-preserving feature extraction over outsourced multimedia data, especially private image data. Since block truncation coding (BTC) is known as a simple and efficient technology for image compression, this paper focuses on privacy-preserving feature extraction in BTC compressed domain. We propose a privacy-preserving computation of BTC feature extraction over massive encrypted images (also called PPBTC). First, all images are uploaded to the cloud after encryption. The privacy-preserving image encryption process consists of block permutation, pixel diffusion, and a bit-plane random shift. BTC features remain unchanged after encryption and the cloud server can directly extract BTC features from the encrypted images. Some analyses and experimental results demonstrate that the proposed privacy-preserving feature extraction scheme for BTCcompressed images is efficient and secure, and it can be applied to secure image computation applications in cloud computing. INDEX TERMS Feature extraction, privacy-preserving, block truncation coding, homomorphic encryption.

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Section: Block Truncation Codingmentioning

confidence: 99%

Secure Outsourcing Algorithm of BTC Feature Extraction in Cloud Computing

Jiang

Yang

2020

IEEE Access

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“…For compression of satellite images, it is performed either directly from the image or from transformed part of the images. As discussed in [1] the compression of satellite images is based on Block Truncation Coding (BTC) technique. It first converts RGB satellite image into HSV planes.…”

Section: Introductionmentioning

confidence: 99%

Compression of High-Resolution Satellite Images Using Optical Image Processing

Patra¹,

Saha²,

Chakraborty³

et al. 2021

Satellite Systems - Design, Modeling, Simulation and Analysis

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This chapter presents a novel method for compressing satellite imagery using phase grating to facilitate the optimization of storage space and bandwidth in satellite communication. In this research work, each Satellite image is first modulated with high grating frequency in a fixed orientation. Due to this modulation, three spots (spectrum) have been generated. From these three spots, by applying Inverse Fourier Transform in any one band, we can recover the image. Out of these three spots, one is center spectrum spot and other spots represent two sidebands. Care should be taken during the spot selection is to avoid aliasing effect. At the receiving end, to recover image we use only one spectrum. We have proved that size of the extracted image is less than the original image. In this way, compression of satellite image has been performed. To measure quality of the output images, PSNR value has been calculated and compared this value with previous techniques. As high-resolution satellite image contains a lot of information, therefore to get detail information from extracted image, compression ratio should be as minimum as possible.

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