Practical Tools for Digital Image Forensic Authentication

Zeng, Jinhua; Lü, Wei; Yang, Rui; Qiu, Xiulian

doi:10.1007/978-981-10-1536-6_59

Cited by 1 publication

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“…Satellite images plays an important part in fields such as weather forecast and land cover classification, demand for fact transmission is necessary for fast acquisition of image thus compression is utilized [7]. In compression quantization is a lossy process used to reduce the information but eliminating or minimize the quantity of high spatial frequencies [8][9][10][11][12][13][14][15] in a DCT applied 8x8 Macro block [16][17][18][19][20][21]. Khowaja et.…”

Section: Introductionmentioning

confidence: 99%

Exhaustive Crisp Parameter Modification in Quantization Table for Effective Image Compression

Siddique

Qadri

Mohy-Ud-Din

2020

Mehran Univ. res. j. eng. technol.

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In recent times, transmission of information over wireless channels is increasing at an exponential rate. Internet is major source of information; it can be in the form of video or images which alone size up to 72% of the global traffic. In order to tackle such immense data, available channel may not be enough for transmission or reception, in this regard it is imperative to use efficient compressions techniques to reduce its size. Compressed image quality depends on the Quantization Table performed after spatial transformation like Discrete Cosine Transform. Size of a raw image captured by Digital Single-Lens Reflex, having all of its traits can easily exceed 20 Mega Bytes. In proposed compression algorithm, a Crisp parameter p modification step is introduced for effective compression of an image by utilizing standard Joint Picture Expert Group Quantization Table as a baseline model. After implementation of the proposed algorithm, Mean Opinion Score is obtained from the masses through an online survey and it provide the scores of 47.633 at p = 1, 62.74 at p = 8, and 83.252 at p = 16. According to Mean opinion score, best trade-off between quality and size of an image is between the values of p ranges from 11-20, this is also proved by Mean Squared Error and Peak Signal to Noise Ratio, as their ranges are 0.00038-0.000301 and 34.09-34.92 dB respectively. Compression Ratio which is from 6.49-5.76 is also acceptable for the given range.

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