14 research outputs found

    JPEG steganography: A performance evaluation of quantization tables

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    The two most important aspects of any image based steganographic system are the imperceptibility and the capacity of the stego image. This paper evaluates the performance and efficiency of using optimized quantization tables instead of default JPEG tables within JPEG steganography. We found that using optimized tables significantly improves the quality of stego-images. Moreover, we used this optimization strategy to generate a 16x16 quantization table to be used instead of that suggested. The quality of stego-images was greatly improved when these optimized tables were used. This led us to suggest a new hybrid steganographic method in order to increase the embedding capacity. This new method is based on both and Jpeg-Jsteg methods. In this method, for each 16x16 quantized DCT block, the least two significant bits (2-LSBs) of each middle frequency coefficient are modified to embed two secret bits. Additionally, the Jpeg-Jsteg embedding technique is used for the low frequency DCT coefficients without modifying the DC coefficient. Our experimental results show that the proposed approach can provide a higher information-hiding capacity than the other methods tested. Furthermore, the quality of the produced stego-images is better than that of other methods which use the default tables

    Adaptive Quantization Matrices for HD and UHD Display Resolutions in Scalable HEVC

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    HEVC contains an option to enable custom quantization matrices, which are designed based on the Human Visual System and a 2D Contrast Sensitivity Function. Visual Display Units, capable of displaying video data at High Definition and Ultra HD display resolutions, are frequently utilized on a global scale. Video compression artifacts that are present due to high levels of quantization, which are typically inconspicuous in low display resolution environments, are clearly visible on HD and UHD video data and VDUs. The default QM technique in HEVC does not take into account the video data resolution, nor does it take into consideration the associated display resolution of a VDU to determine the appropriate levels of quantization required to reduce unwanted video compression artifacts. Based on this fact, we propose a novel, adaptive quantization matrix technique for the HEVC standard, including Scalable HEVC. Our technique, which is based on a refinement of the current HVS-CSF QM approach in HEVC, takes into consideration the display resolution of the target VDU for the purpose of minimizing video compression artifacts. In SHVC SHM 9.0, and compared with anchors, the proposed technique yields important quality and coding improvements for the Random Access configuration, with a maximum of 56.5% luma BD-Rate reductions in the enhancement layer. Furthermore, compared with the default QMs and the Sony QMs, our method yields encoding time reductions of 0.75% and 1.19%, respectively.Comment: Data Compression Conference 201

    Analysis of JPEG Digital Image Compression Process

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    JPEG is the most often used image compression standard that is used since 1992. It is a lossy compression method, and is widely used in digital cameras and mobile phones. Depending on the parameters and user needs, it can achieve a compression ratio between 10 and 50. Memory for digital image storage is saved on the expense of decompressed image quality. The method is based on the Discrete Cosine Transform (DCT) that separates the image into its different frequency components. This paper shows how different parameters of the algorithm influence the performance of the compression. In the end, ideas are given how to either increase the compression ratio keeping the same decompressed image quality, or to improve the quality without decreasing the compression ratio. The quality between the original and the decompressed images is measured using two objective criteria: the Peak Signal-to-Noise Ratio (PSNR) and the structural similarity index (SSIM)

    Image Compression and Watermarking scheme using Scalar Quantization

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    This paper presents a new compression technique and image watermarking algorithm based on Contourlet Transform (CT). For image compression, an energy based quantization is used. Scalar quantization is explored for image watermarking. Double filter bank structure is used in CT. The Laplacian Pyramid (LP) is used to capture the point discontinuities, and then followed by a Directional Filter Bank (DFB) to link point discontinuities. The coefficients of down sampled low pass version of LP decomposed image are re-ordered in a pre-determined manner and prediction algorithm is used to reduce entropy (bits/pixel). In addition, the coefficients of CT are quantized based on the energy in the particular band. The superiority of proposed algorithm to JPEG is observed in terms of reduced blocking artifacts. The results are also compared with wavelet transform (WT). Superiority of CT to WT is observed when the image contains more contours. The watermark image is embedded in the low pass image of contourlet decomposition. The watermark can be extracted with minimum error. In terms of PSNR, the visual quality of the watermarked image is exceptional. The proposed algorithm is robust to many image attacks and suitable for copyright protection applications.Comment: 11 Pages, IJNGN Journal 201

    Minimizing compression artifacts for high resolutions with adaptive quantization matrices for HEVC

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    Visual Display Units (VDUs), capable of displaying video data at High Definition (HD) and Ultra HD (UHD) resolutions, are frequently employed in a variety of technological domains. Quantization-induced video compression artifacts, which are usually unnoticeable in low resolution environments, are typically conspicuous on high resolution VDUs and video data. The default quantization matrices (QMs) in HEVC do not take into account specific display resolutions of VDUs or video data to determine the appropriate levels of quantization required to reduce unwanted compression artifacts. Therefore, we propose a novel, adaptive quantization matrix technique for the HEVC standard including Scalable HEVC (SHVC). Our technique, which is based on a refinement of the current QM technique in HEVC, takes into consideration specific display resolutions of the target VDUs in order to minimize compression artifacts. We undertake a thorough evaluation of the proposed technique by utilizing SHVC SHM 9.0 (two-layered bit-stream) and the BD-Rate and SSIM metrics. For the BD-Rate evaluation, the proposed method achieves maximum BD-Rate reductions of 56.5% in the enhancement layer. For the SSIM evaluation, our technique achieves a maximum structural improvement of 0.8660 vs. 0.8538
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