KEYWORDS: Video, Visualization, Video compression, Motion measurement, Detection and tracking algorithms, Linear filtering, Video processing, Image processing, Motion estimation, Semantic video
This work presents a novel metric and a reliable algorithm for abrupt scene change detection. The new frame difference
metric measures motion and content change across the video by using the motion vector and macroblock information in
the MPEG compressed domain. With this new metric, a reliable scene change detection algorithm is discussed.
Experimental results reveal that our scene change detection algorithm can successfully reduce the false alarms caused
by local frame motion activity and at the same time increase the recall by amplifying the acceptance probability of the
reliable scene change candidate.
JPEG is a common image format in the world wide web. JPEG-compressed images can be used to hide data for secret internet communication and simply any auxiliary data. In this paper, we propose an algorithm called J-Mark to embed invisible watermark information into JPEG compressed images in the compress domain. There are three parts of J-Mark: block selection, DCT coefficient selection, and modification of selected DCT coefficients. Only the texture blocks with significant masking properties are selected in block selection. Only the DCT coefficients with significant energy in the selected blocks are selected. The watermark data are embedded as the 'randomized parity' in the selected DCT coefficients. The embedded data can be recovered perfectly in the compressed domain without fully decoding the JPEG image. Experiment results suggest that the proposed J-Mark can hide the watermarking data without detectable visual artifacts. Although the data hiding capacity differs among images, some parameter of J-Mark can be used to achieve tradeoff between data hiding capacity and visual quality.
In this paper, we propose a novel halftone image data hiding method called Data Hiding in Block Parity (DHBP), which hides the data in the block-sum parity. DHBP assumes that the original multi-tone image is available and the halftoning method is ordered dithering. DHBP can hide a relatively large amount of invisible watermarking data in halftone images while retaining good visual quality. In DHBP, one bit of information is hidden in a block of size MxN by forcing the parity of the sum of the MN pixels to be even or odd according to the data bit to be embedded. To alter the parity, one out of the MN pixels is chosen by minimizing the local image intensity change. Some custom- made quality measures are proposed to evaluate DHBP. Simulation results suggest that DHBP can hide a large amount of data while maintaining good visual quality.
Watermark attacks are first categorized and explained with examples in this paper. We then propose a new image watermark attack called 'Pixel Reallocation Attack'. The proposed attack is a hybrid approach, which aims to decorrelate the embedded watermark with the original watermark. Since many watermarking detections are by correlating the testing image with the target watermark, it will not work once we decorrelate the embedded watermark. For example, the geometrical transformation attacks desynchronize the correlation detector with the testing image leading to detection failure. However, by inserting a template or grid into the watermarked image can make inverse transformation possible and the watermark can be retrieved. If we apply transformations to every single pixel locally, independently and randomly, inverse transformation will not be possible and the attack will be successful since the embedded watermark is not correlated with the original watermark. Experiment shows that single technique approach needs a larger distortion to the image in order to attack the image successfully. We also tested our attack with commercial watermarking software. It cannot detect the watermark after we applied the proposed hybrid attack to the watermarked image.
KEYWORDS: Digital watermarking, Video, Signal detection, Modulation, Image compression, Internet, Distortion, Digital video discs, Image quality, Detection and tracking algorithms
In this paper, we present a new video watermarking technique, which utilize the characteristic of temporal redundancy of video sequence to improve the quality and robustness of the watermarked sequence. The proposed watermarking technique can be combined with many existing 2D image-watermarking algorithm to take advantage of their robustness against various attacks. For every watermark bit (formula available in paper), the pseudo random sequence (formula available in paper) is added to the mid-band coefficients of a block and the complementary sequence, (formula available in paper) is added to the same block in another frame of the insertion pair. To retrieve the embedded watermark bit, the block in the first frame is subtracted by the same block of the second frame, resulting in a watermark with double the magnitude (formula available in paper). Since adjacent video frames are highly correlated and the DCT coefficients are almost the same (especially in non-moving regions), the subtraction of the block pair also cancels out most of the interfering DCT coefficients originated from the host signal, such that the interference to the watermark signal from the host signal is minimized during detection. Experiment shows that the probability of receiving an error bit can be reduced or the picture quality is improved while maintaining the same probability of error.
This paper describes a new highly efficient deinterlacing approach based on motion estimation and compensation techniques. The proposed technique mainly benefits from the motion vector properties of zonal based algorithms, such as the Advanced Predictive Diamond Zonal Search (APDZS) and the Predictive Motion Vector Field Adaptive Search Technique (PMVFAST), multihypothesis motion compensation, but also an additional motion classification phase where, depending on the motion of a pixel, additional spatial and temporal information is also considered to further improve performance. Extensive simulations demonstrate the efficacy of these algorithms, especially when compared to standard deinterlacing techniques such as the line doubling and line averaging algorithms.
Inverse halftoning is a process to recover the multi-tone images from halftone images. Since halftoning is not an invertible process, there is no clear best or unique approach for inverse halftoning. In this paper, we propose a low complexity, high quality Fast Adaptive-spatial-varying Filtering (FAF) for inverse halftoning, which is robust to different kinds of halftone images. FAF is a two-step algorithm combining spatial-variant and spatial invariant filtering. Firstly, it uses spatial invariant filter to suppress the halftone noise and then generates the target image. Secondly, it uses spatial variant filter to filter the halftone image based on the target image. Combining these two filtering, FAF can filter the noise and preserve edges of the halftone image at the same time, which is essential for effective inverse halftoning.
Motion Estimation (ME) is an important part of most video encoding systems, since it could significantly affect the output quality of an encoded sequence. Unfortunately this feature requires a significant part of the encoding time especially when using the straightforward Full Search (FS) algorithm. In this paper a new algorithm is presented named as the Predictive Motion Vector Field Adaptive Search Technique (PMVFAST), which significantly outperforms most if not all other previously proposed algorithms in terms of Speed Up performance. In addition, the output quality of the encoded sequence in terms of PSNR is similar to that of the Full Search algorithm. The proposed algorithm relies mainly upon very robust and reliable predictive techniques and early termination criteria, which make use of parameters adapted to the local characteristics of a frame. Our experiments verify the superiority of the proposed algorithm, not only versus several other well-known fast algorithms, but also in many cases versus even the Full Search algorithm.
KEYWORDS: Halftones, Diffusion, Data hiding, Error analysis, Digital watermarking, Image quality, Visualization, Image processing, Convolution, Lab on a chip
With the ease of distribution of digital images, there is a growing concern for copyright control and authentication. While there are many existing watermarking and data hiding methods for natural images, almost none can be applied to halftone images. In this paper, we proposed a novel data hiding method, Modified Data Hiding Ordered Dithering (MDHED) for halftone images. MDHED is an effective method to hide a relative amount of data while yielding halftone images with good visual quality. Besides, the amount of hidden data is easy to control and the security depends on the key not the system itself.
In this paper a new fast motion estimation algorithm is presented. The algorithm, named as Predictive Diamond Search, is actually based on the Diamond Search (DS) algorithm, which was recently adopted inside the MPEG-4 standard. The DS algorithm, even though faster than most known algorithms, was found not to be very robust in terms of quality for several sequences. By introducing a new predictive criterion and some additional steps in DS, our simulation results show that the proposed algorithm manages to have similar complexity with the DS algorithm, while having superior and more robust quality, similar to that of the Full Search algorithm.
KEYWORDS: Halftones, Data hiding, Diffusion, Visualization, Image quality, Digital watermarking, Printing, Image filtering, Image processing, Signal to noise ratio
With the ease of distribution of digital images, there is a growing concern for copyright control and authentication. While there are many existing watermarking and data hiding methods for natural images, almost none can be applied to halftone images. In this paper, we proposed two novel data hiding methods for halftone images. The proposed Data Hiding Pair-Toggling (DHPT) hides data by forced complementary toggling at pseudo-random locations within a halftone image. It is found to be very effective for halftone images with relatively coarse textures. For halftone images with fine textures (such as error diffusion with Steinberg kernel), the proposed Data Hiding Error Diffusion (DHED) gives significantly better visual quality by integrating the data hiding into the error diffusion operation. Both DHPT and DHED are computationally very simple and yet effective in hiding a relatively large amount of data. Both algorithms yield halftone images with good visual quality.
JPEG is a common image format in the WWW and can potentially be used to hide data for secure internet communication and watermark for copyright control. In this paper, we propose an algorithm to embed the secret or watermark information. The proposed algorithm, named Watermarking by DC Coefficients Modification (WDCM), assumes that the quality factor used in JPEG compression is known. We observe that it is perceptually undetectable if the DC coefficients in certain texture-rich blocks are modified by a small amount. We thus embed the secret information as a binary bit sequence in the quantized DC coefficients in those texture rich blocks. The watermark embedding process can be applied in compression domain without re-encode the data. The information bits are randomized by some pseudo-random noise (PN) sequences, the keys of which are needed for the decoding of the secret information. By embedding the information in the DC components, the proposed algorithm is robust to common JPEG compression if the quality factor is known.
Different multimedia applications and transmission channels require different resolution, frame rates/structures and bitrate, there is often a need to transcode the stored compressed video to suit the needs of these various applications. This paper is concerned about fast motion estimation for frame rate/structure conversion. In this paper, we proposed several novel algorithms that exploit the correlation of the motion vectors in the original video and those in the transcoded video. We achieve a much higher quality than existing fast search algorithms with much lower complexity.
Block based motion estimation is widely used for exploiting temporal correlation within an image. Still the full search algorithm, which is considered to be the optimal, is computational intensive. In this paper a new fast motion estimation method for video coding, is presented. It will be shown that the new algorithm is not only much faster than traditional algorithms, but in some cases can achieve much better visual quality, even from the 'optimal' full search algorithm.
Rate distortion based bit allocation algorithms were previously proposed to yield minimum distortion for a given bit rate in the framework of MPEG. However, they are impractical due to the huge computation required to generate the rate-distortion curve for each image block. In this paper, we propose a fast piecewise linear approximation of the rate distortion function that makes rate-distortion based bit allocation close to practical. By using the proposed fast recursive algorithm to compute selected points on the rate-distortion function and then apply linear interpolation, we show that the computation can be reduced by a factor of approximately 17. Simulation is performed in which rate distortion based bit allocation using bisection approach is applied to an MPEG-1 coder. A significant gain of 1.15dB in PSNR is found to be possible. But the proposed fast algorithm can only achieve a PSNR gain of 0.64dB suggesting that further work is needed.
Recently, MPEG-4 is being formed to study very-low-bit-rate (VLBR) video coding for applications in videotelephony. In this paper, we propose a possible postprocessing technique for VLBR coding. In videophone applications, temporal subsampling is a simple technique which can be combined with other compression schemes to achieve very large compression ratio, so as to satisfy the VLBR requirement. As a result, object motions tend to be jerky and disturbing to the human eyes. To smooth out object motions, we propose a postprocessing technique, motion compensated temporal interpolation (MCTI), to increase the instantaneous decoder frame rate. In MCTI, block-based exhaustive motion search is used to establish temporal association between two reconstructed frames. Both forward and backward searches are used to account for uncovered and newly covered areas properly. With MCTI, we show that one or more frames can be interpolated with acceptable visual quality. After showing the feasibility of MCTI, we propose a fast algorithm FMCTI with reduced computation requirement and negligible performance degradation.
A fast block matching algorithm in the feature domain was proposed by Fok and Au with a computation reduction factor of N/2 for a search block size of N X N. Although the algorithm can achieve close-to-optimal result, it requires a large amount of memory to store the features. This paper presents three improved fast block matching algorithms in the integral projections feature domain which can also reduce the computation significantly but with a considerably lower memory requirement. With a search block size of N X N, two of our algorithms retain a computation reduction factor of N/2 while the other one can achieve a computation reduction factor of N. The three algorithms can achieve close-to-optimal performance in mean absolute difference sense.
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