Wei-Ning Yang

On SVD-based watermarking algorithm

This short communication presents two notes for singular value decomposition (SVD)-based watermarking scheme. The presented notes can increase the invisibility and capacity when embedding the watermark into U and V components of the SVD.

Capacity maximization for reversible data hiding based on dynamic programming approach

Abstract Recently, an efficient reversible lossless data hiding algorithm by Ni et al. was presented. Their fast algorithm can recover the original image without any distortion and its PSNR lower bound is higher than that of all existing reversible data hiding algorithms. Instead of selecting the peak-valley pairs in a greedy way, this paper presents a dynamic programming-based reversible data hiding algorithm to determine the most suitable peak-valley pairs such that the embedding capacity object can be maximized. Based on some artificial map images, experimental results demonstrate that our proposed algorithm has 9% embedding capacity improvement ratio and has the similar image quality performance when compared to Ni et al.’s algorithm although it has some execution-time degradation. For natural images, the embedding capacity of Ni et al.’s algorithm is very close to the maximal embedding capacity obtained by our proposed algorithm. Furthermore, the comparison between our proposed dynamic programming-based algorithm and the reversible data hiding algorithm by Chang et al. is investigated.

Efficient symmetry-based screening strategy to speed up randomized circle-detection

Randomized approaches for circle detections are often used for the advantages of less computational time and memory requirements. However, randomized approaches involve examining a large number of candidate circles and may not be suitable for real-time applications. In this paper, a screening strategy based on the symmetric property of the circle is adopted to select the promising candidates for further investigation, resulting in substantial reduction in the computational time while maintaining the accuracy. Empirical results show that, under the same accuracy level, the proposed symmetry-based method achieves the improvement ratios of 40%-90% on the execution-time when compared to four state-of-the-art randomized methods.

Universal Chroma Subsampling Strategy for Compressing Mosaic Video Sequences With Arbitrary RGB Color Filter Arrays in H.264/AVC

In this paper, we propose a universal chroma subsampling strategy for compressing mosaic video sequences with arbitrary red-green-blue (RGB) color filter arrays (CFAs), which are widely used in the single sensor imaging pipeline, in H.264/AVC. We first develop a modified universal demosaicing scheme, which specifically recovers the G component in the color difference domain, to recover the missing color components in the input mosaic image frames. Then, based on the transform between the RGB and the YUV color spaces, the proposed universal subsampling strategy automatically samples, by considering the significance of the U and V components for reconstructing R and B pixels, the proper U and V chroma components according to the corresponding mosaic structure. To the best of our knowledge, this is the first universal chroma subsampling strategy designed specifically for mosaic video sequences with arbitrary RGB-CFAs. Experimental results on mosaic video sequences with seven common types of the RGB-CFAs demonstrate that the proposed universal chroma subsampling strategy is superior to the conventional strategy of H.264/AVC. Moreover, integrating the proposed universal demosaicing scheme and the chroma subsampling strategy can deliver better video sequence quality.

Reversible data hiding for depth maps using the depth no-synthesis-error model

When embedding hidden data in 3D images, conventional reversible data hiding methods, which are designed for 2D gray and color images, can be applied to color and depth maps. However, directly applying these methods to depth maps may cause synthesis errors and lead to visual artifacts in the rendered virtual views. Two novel reversible data hiding methods based on the depth no-synthesis-error (D-NOSE) model are proposed to embed hidden data in the depth maps of 3D images. The proposed methods can preserve the quality of the rendered virtual view and achieve substantially higher embedding capacity. Experimental results show that the proposed methods achieve better performance than the existing state-of-the-art methods in terms of both embedding capacity and the quality of the rendered virtual views.

Parameter-free based two-stage method for binarizing degraded document images

Binarization plays an important role in document image processing, especially in degraded documents. For degraded document images, adaptive binarization methods often incorporate local information to determine the binarization threshold for each individual pixel in the document image. We propose a two-stage parameter-free window-based method to binarize the degraded document images. In the first stage, an incremental scheme is used to determine a proper window size beyond which no substantial increase in the local variation of pixel intensities is observed. In the second stage, based on the determined window size, a noise-suppressing scheme delivers the final binarized image by contrasting two binarized images which are produced by two adaptive thresholding schemes which incorporate the local mean gray and gradient values. Empirical results demonstrate that the proposed method is competitive when compared to the existing adaptive binarization methods and achieves better performance in precision, accuracy, and F-measure.

Universal intra coding for arbitrary RGB color filter arrays in HEVC

Compressing mosaic video sequences is necessary for storage and transmission over the internet. However, mosaic video sequences with different red-green-blue (RGB) color filter arrays (CFAs) require different compression schemes. We propose a two-stage universal intra coding scheme for compressing mosaic video sequences with arbitrary RGB-CFAs in high efficiency video coding (HEVC). Based on the associated mosaic structure, the proposed scheme first demosaics the neighboring reference pixels and then predicts the color value of the target pixel using the color values of the identical color components in the demosaiced reference pixels. Experimental results demonstrate that the proposed universal intra coding scheme achieves substantial improvement on bitrate while preserving the quality of the reconstructed video sequences.

Novel peer group filtering method based on the CIELab color space for impulse noise reduction

This paper presents a novel peer group filtering method for impulsive noise reduction. The main contributions of the proposed method are twofold. First, noise detection is performed in the CIELab, instead of the RGB, color space to enhance the noise detection effect. Secondly, two different-sized windows are used to determine the peer group for deducing more accurate status of each pixel, alleviating the problem of deducing non-corrupted pixels as corrupted in the neighborhood of edges in the textural regions. Based on five typical test color images, experimental results demonstrate that the proposed method achieves better performance in noise detection and hence noise reduction when compared to five existing competitive methods.

Linear-time prediction mode reduction method for intracoding in H.264/AVC

We present a linear-time elimination method to adaptively reduce the nine intraprediction modes in H.264/AVC to two, three, five, or nine modes while preserving a satisfactory reconstructed video quality. Resemblance between prediction modes and appearing frequency for each prediction mode are first determined in an off-line way from the training video sequences. Prediction modes are modeled as vertices and resemblance between two prediction modes as the weight of the connecting edge in a complete graph. Then, find the Hamilton cycle with the minimum sum of weights. When encoding each intrablock, prediction modes corresponding to the adjacent vertices along the Hamilton cycle are examined for similarity. The prediction mode which appears less frequently in a pair of similar prediction modes is declared as redundant and eliminated. When compared with Laroche et al.’s method which aims to reduce the bitrate, experimental results demonstrate that the proposed elimination method can substantially reduce the execution time while preserving the peak signal-to-noise ratio and bitrate performance.

Bitrate-Saving Intra Coding for Depth Video Compression in H.264/MVC Based on D-NOSE Models

The DIBR technique generates a 3-D perception through a 2-D color and a depth map sequences. Compressing depth map sequence is necessary for storage and transmission considerations. However, the tradeoff between bit rate reduction and quality degradation from compression should be addressed. We propose a bit rate-saving intra coding scheme which modifies, prior to compression, each depth map to minimize the prediction errors. Empirical results show that the proposed intra coding scheme can substantially reduce the bit rate while preserving the quality of the rendered virtual view.