Research on Image Feature Information of Resisting JPEG Compression

2011 ◽  
Vol 121-126 ◽  
pp. 2190-2194
Author(s):  
Chao Kui Wu ◽  
Liang Yong Huang
Keyword(s):  
Image Compression ◽  
Quality Factor ◽  
Discrete Cosine Transform ◽  
Jpeg Compression ◽  
Experimental Results ◽  
Image Feature ◽  
Cosine Transform ◽  
The Third ◽  
Feature Information

To solve the image feature information on the robustness of JPEG compression problems, we use the third layer of wavelet of images to decompose the approximation sub-band coefficients as the image feature information, analyze the characteristics of the discrete cosine transform in JPEG compression so as to compare the robustness of image feature information under different quality of JPEG compression. The experimental results show that: make the image compression quality factor more than the standard JPEG, the approximate sub-band coefficients of image wavelet as the image feature information has better robustness, and their difference is less than or equal to a smaller threshold.

scholarly journals DESIGN OF NEURAL NETWORK AS DATA FLOW MODEL FOR IMAGE COMPRESSION

2013 ◽  
pp. 195-199
Author(s):  
DANESHWARI I. HATTI ◽  
SAVITRI RAJU ◽  
MAHENDRA M. DIXIT
Keyword(s):  
Neural Network ◽  
Image Compression ◽  
Discrete Cosine Transform ◽  
Compression Ratio ◽  
Convergence Time ◽  
Training Algorithms ◽  
Hardware Complexity ◽  
Cosine Transform ◽  
Hidden Neurons

In digital communication bandwidth is essential parameter to be considered. Transmission and storage of images requires lot of memory in order to use bandwidth efficiently neural network and Discrete cosine transform together are used in this paper to compress images. Artificial neural network gives fixed compression ratio for any images results in fixed usage of memory and bandwidth. In this paper multi-layer feedforward neural network has been employed to achieve image compression. The proposed technique divides the original image in to several blocks and applies Discrete Cosine Transform (DCT) to these blocks as a pre-process technique. Quality of image is noticed with change in training algorithms, convergence time to attain desired mean square error. Compression ratio and PSNR in dB is calculated by varying hidden neurons. The proposed work is designed using MATLAB 7.10. and synthesized by mapping on Vertex 5 in Xilinx ISE for understanding hardware complexity. Keywords - backpropagation, Discrete

scholarly journals An Improved Robust and Adaptive Watermarking Algorithm Based on DCT

2012 ◽  
Vol 10 (3) ◽  
Author(s):  
Q. Zhang ◽  
Y. Li ◽  
X. Wei
Keyword(s):  
Discrete Cosine Transform ◽  
Chaotic System ◽  
Jpeg Compression ◽  
Experimental Results ◽  
Stego Image ◽  
Embedding Method ◽  
Cosine Transform ◽  
Adaptive Watermarking ◽  
Adaptive Embedding ◽  
Dct Coefficients

This paper proposes an improved watermarking algorithm based on DCT(Discrete Cosine Transform). We carried out the algorithm as described as follows. First, we extended both rows and ranks of the watermark by using the proposed method before the embedding stage. After expansion, Sine chaotic system is employed in encrypting the watermark. In the embedding stage, an effective and adaptive embedding method is proposed to embed the watermark into the blocked DCT coefficients. Experimental results demonstrate that the proposed algorithm in this paper works well in resisting both geometry attack and noise attack. It also does well in recovering the watermark after stego image suffered from JPEG compression.

scholarly journals Estimating Previous Quantization Factors on Multiple JPEG Compressed Images

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Sebastiano Battiato ◽  
Oliver Giudice ◽  
Francesco Guarnera ◽  
Giovanni Puglisi
Keyword(s):  
Image Quality ◽  
Discrete Cosine Transform ◽  
Jpeg Compression ◽  
Compression Algorithm ◽  
Experimental Results ◽  
The Other ◽  
Cosine Transform ◽  
Novel Technique ◽  
Compressed Images ◽  
Acquisition Device

AbstractThe JPEG compression algorithm has proven to be efficient in saving storage and preserving image quality thus becoming extremely popular. On the other hand, the overall process leaves traces into encoded signals which are typically exploited for forensic purposes: for instance, the compression parameters of the acquisition device (or editing software) could be inferred. To this aim, in this paper a novel technique to estimate “previous” JPEG quantization factors on images compressed multiple times, in the aligned case by analyzing statistical traces hidden on Discrete Cosine Transform (DCT) histograms is exploited. Experimental results on double, triple and quadruple compressed images, demonstrate the effectiveness of the proposed technique while unveiling further interesting insights.

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