اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدA novel technique for image steganography based on Block-DCT and Huffman Encoding
188
0
0.0
(
0
)
نشر من قبل
Secretary Aircc Journal
تاريخ النشر
2010
مجال البحث
الهندسة المعلوماتية
والبحث باللغة
English
تأليف
A.Nag
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
Image steganography is the art of hiding information into a cover image. This paper presents a novel technique for Image steganography based on Block-DCT, where DCT is used to transform original image (cover image) blocks from spatial domain to frequency domain. Firstly a gray level image of size M x N is divided into no joint 8 x 8 blocks and a two dimensional Discrete Cosine Transform (2-d DCT) is performed on each of the P = MN / 64 blocks. Then Huffman encoding is also performed on the secret messages/images before embedding and each bit of Huffman code of secret message/image is embedded in the frequency domain by altering the least significant bit of each of the DCT coefficients of cover image blocks. The experimental results show that the algorithm has a high capacity and a good invisibility. Moreover PSNR of cover image with stego-image shows the better results in comparison with other existing steganography approaches. Furthermore, satisfactory security is maintained since the secret message/image cannot be extracted without knowing decoding rules and Huffman table.
قيم البحث
اقرأ أيضاً
This paper provides a technical overview of a deep-learning-based encoder method aiming at optimizing next generation hybrid video encoders for driving the block partitioning in intra slices. An encoding approach based on Convolutional Neural Network
s is explored to partly substitute classical heuristics-based encoder speed-ups by a systematic and automatic process. The solution allows controlling the trade-off between complexity and coding gains, in intra slices, with one single parameter. This algorithm was proposed at the Call for Proposals of the Joint Video Exploration Team (JVET) on video compression with capability beyond HEVC. In All Intra configuration, for a given allowed topology of splits, a speed-up of $times 2$ is obtained without BD-rate loss, or a speed-up above $times 4$ with a loss below 1% in BD-rate.
The widely used adaptive HTTP streaming requires an efficient algorithm to encode the same video to different resolutions. In this paper, we propose a fast block structure determination algorithm based on the AV1 codec that accelerates high resolutio
n encoding, which is the bottle-neck of multiple resolutions encoding. The block structure similarity across resolutions is modeled by the fineness of frame detail and scale of object motions, this enables us to accelerate high resolution encoding based on low resolution encoding results. The average depth of a blocks co-located neighborhood is used to decide early termination in the RDO process. Encoding results show that our proposed algorithm reduces encoding time by 30.1%-36.8%, while keeping BD-rate low at 0.71%-1.04%. Comparing to the state-of-the-art, our method halves performance loss without sacrificing time savings.
Due to differences in frame structure, existing multi-rate video encoding algorithms cannot be directly adapted to encoders utilizing special reference frames such as AV1 without introducing substantial rate-distortion loss. To tackle this problem, w
e propose a novel bayesian block structure inference model inspired by a modification to an HEVC-based algorithm. It estimates the posterior probabilistic distributions of block partitioning, and adapts early terminations in the RDO procedure accordingly. Experimental results show that the proposed method provides flexibility for controlling the tradeoff between speed and coding efficiency, and can achieve an average time saving of 36.1% (up to 50.6%) with negligible bitrate cost.
We propose an image steganographic algorithm called EncryptGAN, which disguises private image communication in an open communication channel. The insight is that content transform between two very different domains (e.g., face to flower) allows one t
o hide image messages in one domain (face) and communicate using its counterpart in another domain (flower). The key ingredient in our method, unlike related approaches, is a specially trained network to extract transformed images from both domains and use them as the public and private keys. We ensure the image communication remain secret except for the intended recipient even when the content transformation networks are exposed. To communicate, one directly pastes the `message image onto a larger public key image (face). Depending on the location and content of the message image, the `disguise image (flower) alters its appearance and shape while maintaining its overall objectiveness (flower). The recipient decodes the alternated image to uncover the original image message using its message image key. We implement the entire procedure as a constrained Cycle-GAN, where the public and the private key generating network is used as an additional constraint to the cycle consistency. Comprehensive experimental results show our EncryptGAN outperforms the state-of-arts in terms of both encryption and security measures.
Explanation from Sai Ma: The experiments in this paper are conducted on Caffe framework. In Caffe, there is an API to directly set the gradient in Matlab. I wrongly use it to control the probability, in fact, I modify the gradient directly. The misus
age of API leads to wrong experiment results, and wrong theoretical analysis. Apologize to readers who have read this paper. We have submitted a correct version of this paper to Multimedia Tools and Applications and it is under revision. Thanks to Dr. Patrick Bas, who is the Associate Editor of TIFS and the anonymous reviewers of this paper. Thanks to Tingting Song from Sun Yat-sen University. We discussed some problems of this paper. Her advice helps me to improve the submitted paper to Multimedia Tools and Applications.
الأسئلة المقترحة
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
