Reference Pixels Research Articles

基于像素差和索引函数的信息隐藏算法

在2 × 2像素块中，参考像素值由索引函数随机确定，然后计算参考像素与其周围的其它三个像素值的差，根据像素差所处的划分范围决定嵌入像素的秘密信息比特数。利用余函数嵌入秘密信息有效地减少载密图像的失真度，在提取信息的过程中，量化后的像素值能准确的提取秘密信息。改进了Jung和Yoo提出的基于索引函数信息隐藏算法，使算法更具有安全性。 In the 2 × 2 pixel block, reference pixel values was randomly determined by the index function, And we calculated the pixel value difference between reference pixel value and the other three pixel value around it. The number of secret data was embedded according to the range of pixel value difference. Using complementary function embedded secret information to effectively re-duce the load of image distortion degree. In the process of extracting information, the quantitative pixel values can accurately extract the secret information. Our proposed method improves the Jung and Yoo information hiding algorithm based on index function, and the proposed algorithm has more security.

Image interpolation based high capacity reversible data hiding scheme

In this paper, we propose a new interpolation technique which considers all the neighboring pixels as well as their impact on the reference pixels to provide better quality interpolated image and a new data hiding scheme which embeds the secret data in the interpolated pixels by taking into account the human visual system so that quality of the resultant image is maintained. The proposed interpolation technique is an improvement of the existing neighbor mean interpolation (NMI) technique in such a way that the interpolated image would have more resemblance to the input image. The proposed interpolation technique has less computational cost like NMI as it does not perform much computation during estimation unlike B-Spline, Bilinear Interpolation etc. The proposed data hiding scheme comes into the category of reversible data hiding scheme as the input image can be reconstructed after extraction of the entire secret data at the receiver side. Thus, it reduces the communication cost. Furthermore, the proposed data hiding scheme identifies the smooth and complex regions of the interpolated (or cover) image by dividing the same into blocks. It then embeds more bits into the complex regions of the image so that data hiding capacity as well as the image quality can be enhanced. The experimental results shows that the percentage increment in the PSNR value and capacity of the proposed scheme with respect to Chang et al. method is in the range of 0.26 to 30.60% and 0.87 to 73.82%, respectively. Moreover, the modified NMI yields higher PSNRs than other interpolating methods such as NMI, BI, and ENMI.

Gender classification from facial images using gray relational analysis with novel local binary pattern descriptors

Gender classification (GC) is one of the major tasks in human identification that increase its accuracy. Local binary pattern (LBP) is a texture method that employed successfully. But LBP suffers a major problem; it cannot capture spatial relationships among local textures. Therefore, in order to increase the accuracy of GC, two LBP descriptors, which are based on (1) spatial relations between neighbors with a distance parameter, and (2) spatial relations between a reference pixel and its neighbor on the same orientation, were employed to extract features from facial images. Additionally, gray relational analysis (GRA) was carried out to identify gender through extracted features. Experiments on the FEI database illustrated the effectiveness of the proposed approaches. Achieved accuracies are 97.14, 93.33, and 92.50% by applying GRA with the nLBP\(_{d}\), dLBP\(_{\alpha }\), and traditional LBP features, respectively. Experimental results indicated that the proposed approaches were very competitive feature extraction methods in GC. Present work also showed that the nLBP\(_{d}\), dLBP\(_{\alpha }\) methods were obtained more acceptable results than traditional LBP.

Local Multi Code Pattern Generation for Face Identification

AbstractThe existing LTrP method shows the relationship between the reference pixel and its neighbor’s, based on the four directional code that are computed using the first-order derivatives in both vertical and horizontal directions. It is apparent that the performance of LTrP can be improved by differentiating the edges in more than four directions. This observation has motivated us to propose a nine direction code referred to as Local Multi Code Pattern (LMCP). LMCP extracts supplementary directional information as compared with LTrP. The performance analysis of the aforementioned techniques were done with the help of ORL, Yale, Jaffee databases and also the recital analysis on the same significantly improves the recognition rate of the proposed method.

Reversible data hiding based on multilevel histogram modification and pixel value grouping

This paper proposes a multilevel histogram modification based reversible data hiding scheme using a new difference generation strategy called pixel value grouping (PVG). It aims to produce shaper difference histogram by exploiting the high correlation among pixels within block. After sorting, pixel values are grouped according to their distribution. For each set of similar pixel values, real or virtual reference pixel will be determined to compute differences in the scope of pixel values group and next secret message is embedded through expansion embedding. By PVG, we success to greatly reduce the number of to-be-shifted pixels while producing sufficient EC and hence less distortion can be introduced for embedding the same payload. Moreover, the same grouping can be achieved at the decoder and the real or virtual reference pixel can be determined without any prior knowledge, which guarantees the reversibility. Experimental results demonstrate that our scheme outperforms previous related state-of-the-art schemes.

Study on radiometric intercalibration methods for DMSP-OLS night-time light imagery

ABSTRACTThe Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) night-time light image sets has been successfully used in various fields to monitor temporal and spatial distributions, such as urbanization and socioeconomic activities. However, the radiometric calibration of night-time light images has long been a problem that limits the application of night-time light image sets in multi-temporal analyses. The key to an intercalibration model is to automatically extract the reference pixels with stable lights and to simultaneously remove unstable (or variant) light pixels viewed as outliers (or gross error). This paper systemically compares five weighted least squares regression (WLSR) algorithms for radiometric intercalibration to determine the method with the highest accuracy, including (1) classic methods: empirical rule (ER), Danish method (DM), and posterior variance estimation (PVE); and (2) state-of-the-art methods: random sample consensus (RANSAC) and least median of squares (LMedS). Moreover, a more objective adjusted root mean square error (RMSE) method is proposed to evaluate accuracy. Through the experiments, we systemically analyse the performance of different estimators and propose recommendations for optimizing intercalibration for specific applications. Moreover, the study reveals that gross error approximatively obeys the stochastic or expansion model in the radiometric intercalibration of DMSP-OLS image sets. Overall, LMedS works best and is proposed to intercalibrate the radiometric values of night-time light image sets.

Exploring deep gradient information for biometric image feature representation

This paper presents a novel but simple biometric image feature representation method, called exploring deep gradient information (DGI). DGI first captures the local structure of an image by computing the histogram of gradient orientation of each macro-pixel (local patch around the reference pixel). Thus, one image can be decomposed into L sub-images (sub-orientation images) according to the gradient information of each macro-pixel since there are L bins in the local histogram. To enrich the gradient information, we also consider the gradient orientation and magnitude of original image as sub-images. For each sub-image, histogram of oriented gradient (HOG) is used to further explore the gradient orientation information. All HOG features are concatenated into one augmented super-vector. Finally, fisher linear discriminate analysis (FLDA) is applied to obtain the low-dimensional and discriminative feature vector. We evaluated the proposed method on the real-world face image datasets NUST-RWFR, Pubfig and LFW, the PolyU Finger-Knuckle-Print database and the PolyU Palmprint database. Experimental results clearly demonstrate the effectiveness of the proposed DGI compared with state-of-the-art algorithms, e.g., SIFT, HOG, LBP, POEM, LARK and IDLS.

하드웨어 기반 HEVC 인트라 인코더에서 다운 샘플링을 사용한 고속 Rough Mode Decision

HEVC #$%H ?@ABCDE51.4FGDHIJ . @ABCD:KLM4N OPQRS TUV W. XErough mode decision(RMD) Y ZV[. \Z&]:^GMrate-distortion optimization (RDO) _GBCDI`abRMD:cd<OefY78RDO g@:Mhi]S ^G. jklm n&opS&qrRMD _Gs=@ABCD:tuvwIx. yzbERMD _G{|}~I€, ‚}~ƒ„E_GZJ 7 {|<† Ze%RMD f‡34@Aˆ70%Iˆtu6x[. aBDBR HIE0.04%8‰‰6$ . TUYRMD ZŠ‹ Œ E533%, Ž&E566% t .AbstractHEVC is the next compression standard and is expected to be used widely replacing the conventional H.264/AVC standard. The compression ratio of the HEVC is twice times than H.264/AVC, whereas its computational complexity is increased by up to 40%. Many research efforts have been made to reduce the computational complexity and to speed up encoding. For intra coding, the rough mode decision (RMD) is commonly applied. The rate-distortion optimization (RDO) process to decide the best mode is too complex so that RMD chooses the candidate modes with a simple process and sends the candidates to RDO process. However, for large-size blocks, the RMD also requires considerable computations. In this paper, a down-sampling scheme is proposed for the RMD process. The reference pixel loading, predicted pixel generation are performed using the down-sampled pixel data. When the proposed scheme is applied to the RMD, the computational complexity is reduced by 70% with a marginal bitrate increase of 0.04%. In terms of area of hardware-based RMD, the gate count and the buffer size is reduced 33% and 66%, respectively.Keyword : Down-sampling, Rough mode decision, HEVC, intra prediction

Improving Intra Prediction in High-Efficiency Video Coding.

Intra prediction is an important tool in intra-frame video coding to reduce the spatial redundancy. In current coding standard H.265/high-efficiency video coding (HEVC), a copying-based method based on the boundary (or interpolated boundary) reference pixels is used to predict each pixel in the coding block to remove the spatial redundancy. We find that the conventional copying-based method can be further improved in two cases: 1) the boundary has an inhomogeneous region and 2) the predicted pixel is far away from the boundary that the correlation between the predicted pixel and the reference pixels is relatively weak. This paper performs a theoretical analysis of the optimal weights based on a first-order Gaussian Markov model and the effects when the pixel values deviate from the model and the predicted pixel is far away from the reference pixels. It also proposes a novel intra prediction scheme based on the analysis that smoothing the copying-based prediction can derive a better prediction block. Both the theoretical analysis and the experimental results show the effectiveness of the proposed intra prediction method. An average gain of 2.3% on all intra coding can be achieved with the HEVC reference software.

Asymmetric occlusion detection using linear regression and weight‐based filling for stereo disparity map estimation

Stereo matching computes the disparity information from stereo image pairs. A number of stereo matching methods have been proposed to estimate a fine disparity map. However, objects present in the images are occluded on account of different camera viewpoints in a stereo vision setup, and hence it is quite difficult to get a fine disparity map. The methods which use disparity map information of two cameras (symmetric approach) to detect occluded pixels are computationally more complex. The authors approach entails to detect the occluded pixels only by using single disparity map information (asymmetric approach). The behaviour of reference and target pixels are analysed, and it is observed that the target matching pixels almost follow a linear pattern with respect to the reference image pixels. Hence, it is approximated by a linear regression model, and subsequently this model is used to detect the occluded pixels in the authors’ method. Finally, a fine disparity map is obtained by incorporating a novel occlusion filling method. Experimental results show that the proposed occlusion detection method gives almost similar performance as that of the methods which use two disparity maps for detection. For occlusion filling, the authors utilise support weights from both the stereo images, and hence their method can give better performance.

4K Real-Time HEVC Decoder on an FPGA

With the popularization of a quad high-definition/4K video being dependent on the availability of real-time High Efficiency Video Coding (HEVC) decoders, hardware implementations have become more appealing due to their superior performance and low power consumption. In this paper, a field-programmable gate array (FPGA)-based hardware implementation of a 4K 30 frames/s real-time HEVC decoder is presented. An elastically pipelined decoder architecture is used to absorb variations in processing time and each pipeline stage is optimized to use available FPGA primitives. FPGA-specific challenges in managing critical path delays to achieve a target operating frequency of 150 MHz required many architectural novelties, such as exploitation of the sparsity of transformed coefficient matrix, single-cycle reference pixel processing in intra prediction, and flexible <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$8 \times 8$ </tex-math></inline-formula> block ordering in deblocking filter/sample adaptive offset filter. A high-throughput latency-aware cache architecture was used to reduce the external dynamic RAM access bandwidth by 70%. This work is compliant with the HEVC main profile at level 5 of the HEVC standard and only consumes 126K lookup tables, 58K registers, and 335 18-kb block RAMs when implemented on Xilinx Zynq 7045.

Local directional gradient pattern: a local descriptor for face recognition

In this paper a local pattern descriptor in high order derivative space is proposed for face recognition. The proposed local directional gradient pattern (LDGP) is a 1D local micropattern computed by encoding the relationships between higher order derivatives of the reference pixel in four distinct directions. The proposed descriptor identifies relationship between the high order derivatives of the referenced pixel in four different directions to compute the micropattern which corresponds to the local feature. Proposed descriptor considerably reduces the length of the micropattern which consequently reduces the extraction time and matching time while maintaining the recognition rate. Results of the extensive experiments conducted on benchmark databases AT&T, Extended Yale B and CMU-PIE show that the proposed descriptor significantly reduces the extraction as well as matching time while the recognition rate of the descriptor is almost similar to existing state of the art methods. Moreover the proposed descriptor is more resistant against the AWGN compared to the other state of the art descriptors used for face recognition problems.

Multi-quantized local binary patterns for facial gender classification

This paper presents multi-quantized local binary patterns for facial gender classification. For encoding the gray level difference (GLD) between a reference pixel and its neighbors, local binary pattern employs a binary quantization which retains the sign of GLD but discards the magnitude information. To improve the discrimination capability, the proposed method utilizes both the sign and magnitude components by performing multi-level vector quantization of GLD. Each quantized level is then separately encoded to generate multiple local binary patterns. The proposed method is evaluated on four publicly available datasets (FERET, PAL, CASIA and FEI) through extensive experiments. Comparison of performance with various existing methods clearly demonstrated that the proposed method has advantages such as higher discrimination power, improved noise robustness and better generalization capability.

Local rank-based spatial information for improvement of remote sensing hyperspectral imaging resolution

This paper shows the effect of using local rank and selectivity constraints based on spatial information of spectroscopic images to increase the performance of Multivariate Curve Resolution (MCR) methods and to decrease the ambiguity of final results. Fixed Size Image Window-Evolving Factor Analysis (FSIW-EFA) is applied to discover which pixels are more suitable for the application of local rank constraints. An automated method to help in setting appropriate threshold values for the application of FSIW-EFA, based on global and local use of Singular Value Decomposition (SVD) is proposed. Additional use of correlation coefficients between selected reference spectra and pixel spectra of the image is shown to provide an alternative way for the application of the selectivity constraint in spectroscopic images for the first time. This alternative method resulted to be satisfactory when pure pixels exist.

Spatio-Temporally Consistent Color and Structure Optimization for Multiview Video Color Correction

When compared to conventional 2-D video, multiview video can significantly enhance the visual 3-D experience in 3-D applications by offering horizontal parallax. However, when processing images originating from different views, it is common that the colors between the different cameras are not well- calibrated . To solve this problem, a novel energy function -based color correction method for multiview camera setups is proposed to enforce that colors are as close as possible to those in the reference image but also that the overall structural information is well-preserved. The proposed system introduces a spatio-temporal correspondence matching method to ensure that each pixel in the input image gets bijectively mapped to a reference pixel. By combining this mapping with the original structural information, we construct a global optimization algorithm in a Laplacian matrix formulation and solve it using a sparse matrix solver. We further introduce a novel forward-reverse objective evaluation model to overcome the problem of lack of ground truth in this field. The visual comparisons are shown to outperform state-of-the-art multiview color correction methods, while the objective evaluation reports PSNR gains of up to 1.34 dB and SSIM gains of up to 3.2%, respectively.

A Novel Mean Median Filter for Noise and Artifacts Suppression from Digital Images

A novel mean-median filter is proposed for the suppression of impulse noise and various artifacts from the digital images. Leading Diagonal Sorting Algorithm is used with the fixed 3x3 size working window to compute the median. Truncated mean is computed by defining the boundaries and truncating the pixel values in the filtering window that fall outside the defined boundary. Noise detection is carried in two steps: In the first step the ‘reference pixel’ is tested for the presence of impulses with Min-Max detection strategy. In the second stage of detection, edge preserving unique criteria is employed to further classify the pixel under test as ‘noisy’ or ‘edge belonged’. This intelligent edge preserving decision criterion decides whether the test pixel deserves the restoration or not and facilitates the restoration of the noisy pixel either by the ‘truncated mean’ or by the ‘window median’ based on the decision threshold. Performance of the proposed filter algorithm is studied on a large number of images with varying amounts of salt and pepper noise and several types of artifacts and their combinations. Simulation results prove that the proposed algorithm (PA) effectively suppresses the high density salt and pepper noise (SPN) and in addition, it performs excellent in suppressing image artifacts such as strip lines (both white and black), drop lines (both white and black), missing bands and noise blotches. The novelty of the proposed mean-median filter lies in the fact that it attempts to simultaneously suppress impulsive noise and artifacts with good edge preservation (as the maximum size of the filtering window is restricted to ‘3×3’ only) and also because a two stage detection mechanism is employed. The goodness of the proposed algorithm lies in replacing several independent filter schemes required for suppression of noise and artifacts of several types without much distorting the vital features of the image under test. The performance evaluation of the proposed algorithm is done in terms visual appearance and quantitative measures such as Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Image Enhancement Factor (IEF) and the Computation Time (CT). Simulation results are compared with other state of art algorithms to derive the meaningful conclusions. General Terms Image Processing, Noise and Artifacts Suppression.

Automatic Boat Identification System for VIIRS Low Light Imaging Data

The ability for satellite sensors to detect lit fishing boats has been known since the 1970s. However, the use of the observations has been limited by the lack of an automatic algorithm for reporting the location and brightness of offshore lighting features arising from boats. An examination of lit fishing boat features in Visible Infrared Imaging Radiometer Suite (VIIRS) day/night band (DNB) data indicates that the features are essentially spikes. We have developed a set of algorithms for automatic detection of spikes and characterization of the sharpness of spike features. A spike detection algorithm generates a list of candidate boat detections. A second algorithm measures the height of the spikes for the discard of ionospheric energetic particle detections and to rate boat detections as either strong or weak. A sharpness index is used to label boat detections that appear blurry due to the scattering of light by clouds. The candidate spikes are then filtered to remove features on land and gas flares. A validation study conducted using analyst selected boat detections found the automatic algorithm detected 99.3% of the reference pixel set. VIIRS boat detection data can provide fishery agencies with up-to-date information of fishing boat activity and changes in this activity in response to new regulations and enforcement regimes. The data can provide indications of illegal fishing activity in restricted areas and incursions across Exclusive Economic Zone (EEZ) boundaries. VIIRS boat detections occur widely offshore from East and Southeast Asia, South America and several other regions.

Interactive Segmentation of Color Images Based on Color Saliency

SUMMARYEfficient interactive foreground extraction from color images is of great practical importance in computer vision. In recent years, an approach based on optimization using graph‐cuts has been widely used. However, an interactive foreground extraction approach, which is intuitive and efficient for users, is required for practical applications. In this paper, we propose a novel interactive foreground extraction method based on color saliency. In our method, the user provides only some foreground pixels as the initial reference. To achieve extraction of multiple target objects, the likelihoods of the foreground and background are defined by a Gaussian mixture model and a color saliency map based on the provided reference pixels. These likelihoods are added to the cost of the proposed graph. Finally, image segmentation is performed by optimizing the proposed graph using the graph‐cut algorithm.

Directional local ternary patterns for multimedia image indexing and retrieval

In this paper, we proposed a novel multimedia image indexing and retrieval algorithm using Directional Local Ternary Pattern (DLTP) for Content-Based Image Retrieval (CBIR). The standard Local Binary Pattern (LBP) and Local Ternary Pattern (LTP) encode the relationship between reference pixel and its surrounding neighbours by computing grey-level difference. The proposed method extracts the directional edge information based on local ternary value (−1, 0, 1) instead of binary value (0, 1) in 0°, 45°, 90°, and 135° directions of an image. The performance of the proposed method is compared with local binary pattern LBP, Block-based LBP (BLK-LBP), Centre-Symmetric LBP (CS-LBP), Local Edge Patterns for Segmentation (LEPSEG), Local Edge Patterns for Image Retrieval (LEPINV) and other existing transform domain methods based on Corel-5000 (DB1) and Corel-10000 (DB2) databases. The retrieval performance of DLTP shows better improvement in terms of their performance measures as compared with the standard LBP.

A New Reversible Data Hiding Scheme with Improved Capacity Based on Directional Interpolation and Difference Expansion

Using reversible data hiding (RDH) we can hide our secret data into a cover image and the receiver can restore both the secret data and the original image. It has wide application in medical imagery, military imagery where no distortion of original cover is allowed. Hong and Chen proposed a RDH scheme based on interpolation and histogram shifting. In their scheme reference pixels are not used for data embedding which leads to low capacity. Huang et al. modified this scheme and proposed a high capacity RDH scheme in which prediction errors are used for data embedding. In this paper we propose a further modification to the scheme of Huang et al. based on directional interpolation. Directional interpolation yields a better approximation to the original pixel which improves the capacity of embedding. The effectiveness of the proposed scheme is tested using standard test images and the proposed scheme gives better results in terms of embedding capacity and visual quality compared to Huang et al. scheme.