Suxia Cui

Mesh-based motion estimation and compensation in the wavelet domain using a redundant transform

A technique is presented that incorporates an irregular triangle mesh into wavelet-domain motion-estimation and motion-compensation using a shift-invariant redundant wavelet transform. Triangle vertices are identified by a simple correlation operator locating image edges in the wavelet subbands, while motion compensation takes place through an affine transformation mapping triangles from one frame to the next. The motion-compensated residual is downsampled to a non-redundant form which is then coded using any wavelet-based still-image coder. Experimental results indicate that the combined approach outperforms either technique applied separately,, in addition, the proposed method outperforms a variety of motion-estimation and motion-compensation approaches operating in both the spatial and wavelet domains.

Multihypothesis motion compensation in the redundant wavelet domain

Multihypothesis motion compensation is extended into the transform domain by using a redundant wavelet transform to produce multiple predictions that are diverse in transform phase. The corresponding inverse transform implicitly combines the multihypothesis predictions into a single spatial-domain prediction for motion compensation such that no side information is needed to describe the combination weights. Additionally, we use a hierarchical search to tailor the motion-vector field to individual phases. Substantial gains in rate-distortion performance are obtained in comparison to an equivalent system using single-phase prediction.

3D video coding using redundant-wavelet multihypothesis and motion-compensated temporal filtering

A video coder is presented that combines mesh-based motion-compensated temporal filtering, phase-diversity multihypothesis motion compensation, and an embedded 3D wavelet-coefficient coder. The key contribution of this work is the introduction of the phase-diversity multihypothesis paradigm into motion-compensated temporal filtering, which is achieved by deploying temporal filtering in the domain of a spatially redundant wavelet transform. A regular triangle mesh is used to track motion between frames, and an affine transform between mesh triangles implements motion compensation within a lifting-based temporal transform. Experimental results reveal that the incorporation of pulse-diversity multihypothesis into mesh-based motion-compensated temporal filtering significantly improves the rate-distortion performance of the 3D video coder.

3-D video coding with redundant-wavelet multihypothesis

Multihypothesis with phase diversity is introduced into motion-compensated temporal filtering by deploying the latter in the domain of a spatially redundant wavelet transform. The centerpiece of this redundant-wavelet approach to multihypothesis temporal filtering is a multiple-phase inverse transform that involves an implicit projection significantly reducing noise not captured by the motion model of the temporal filtering. The primary contribution of the work is a derivation that establishes analytically the advantage of the redundant-wavelet approach as compared to equivalent temporal filtering taking place in the spatial domain. For practical implementation, a regular triangle mesh is used to track motion between frames, and an affine transform between mesh triangles implements motion compensation within a lifting-based temporal transform. Experimental results reveal that the incorporation of phase-diversity multihypothesis into motion-compensated temporal filtering improves rate-distortion performance, and state-of-the-art scalable performance is observed.

Motion Compensation Via Redundant-Wavelet Multihypothesis

Multihypothesis motion compensation has been widely used in video coding with previous attention focused on techniques employing predictions that are diverse spatially or temporally. In this paper, the multihypothesis concept is extended into the transform domain by using a redundant wavelet transform to produce multiple predictions that are diverse in transform phase. The corresponding multiple-phase inverse transform implicitly combines the phase-diverse predictions into a single spatial-domain prediction for motion compensation. The performance advantage of this redundant-wavelet-multihypothesis approach is investigated analytically, invoking the fact that the multiple-phase inverse involves a projection that significantly reduces the power of a dense-motion residual modeled as additive noise. The analysis shows that redundant-wavelet multihypothesis is capable of up to a 7-dB reduction in prediction-residual variance over an equivalent single-phase, single-hypothesis approach. Experimental results substantiate the performance advantage for a block-based implementation

A UGV-based laser scanner system for measuring tree geometric characteristics

This paper introduces a laser scanner based measurement system for measuring crop/tree geometric characteristics. The measurement system, which is mounted on a Unmanned Ground Vehicle (UGV), contains a SICK LMS511 PRO laser scanner, a GPS, and a computer. The LMS511 PRO scans objects within distance up to 80 meters with a scanning frequency of 25 up to 100Hz and with an angular resolution of 0.1667° up to 1°. With an Ethernet connection, this scanner can output the measured values in real time. The UGV is a WIFI based remotely controlled agricultural robotics system. During field tests, the laser scanner was mounted on the UGV vertically to scan crops or trees. The UGV moved along the row direction with certain average travel speed. The experimental results show that the UGVs travel speed significantly affects the measurement accuracy. A slower speed produces more accurate measuring results. With the developed measurement system, crop/tree canopy height, width, and volume can be accurately measured in a real-time manner. With a higher spatial resolution, the original data set may even provide useful information in predicting crop/tree growth and productivity. In summary, the UGV based measurement system developed in this research can measure the crop/tree geometric characteristics with good accuracy and will work as a step stone for our future UGV based intelligent agriculture system, which will include variable rate spray and crop/tree growth and productivity prediction through analyzing the measured results of the laser scanner system.

Using redundant wavelet transform in video watermarking

This paper presents a scheme that apply the pixel-wise masking technique used in image watermarking into video sequence. The proposed algorithm deploys the video watermarking in the redundant discrete wavelet transform (RDWT) domain. The advantages of using an overcompleted wavelet transform instead of the traditional critically subsampled discrete wavelet transform (DWT) are discussed. The redundancy in the transform domain facilitates a better detection of the video texture characteristics in a video sequence. Thus leads to an efficient watermark casting scheme, in which more strength of watermark can be embedded into the video sequence, but still not perceivable. Different methods of using RDWT or DWT coefficients to add the watermarking are compared. Experimental results show that RDWT domain video watermarking offers greater robustness than DWT domain method.

Image object removal in redundant wavelet transform domain

In this paper, we present a novel approach on image object removal by extending subpatch texture synthesis technique into redundant wavelet transform (RDWT) domain. As an overcompleted wavelet transform, RDWT is shift invariant and obtained without downsampling. Also, each RDWT highpass subband exhibits one specific orientation features of the image, in horizontal, vertical, or diagonal. All these make RDWT ideal for performing texture synthesis object removal techniques. In our experiments, subpatch texture synthesis in RDWT is introduced to remove unwanted objects from digital photographs. Specifically, for each RDWT subband, depending on the subband orientation, a particular direction subpatch texture synthesis is applied independently. Experimental results reveal that our simple algorithm performs better than previous methods.

Redundant Wavelet Transform in Biomedical Image Application

The change of blood vessel is very important in the biomedical research, because creatures, including human beings tempt to adjust themselves to fit for the new environments. For example, if a tumor was found inside a human body and diagnosed as cancer, to get rid of this tumor is important, but to prevent the tumor to reach out to other organs is more crucial. The goal of starving the tumor can be achieved by preventing new blood vessels to grow into it. Another example is the wound healing which can be enhanced by encouraging blood vessels to reach the damaged parts. Both applications focus on the trace of the growing blood vessels. There are several trials on how to trace blood vessels, we can category them into three main approaches: window-based methods, classifier-based methods and tracking-based methods [1]. In this paper, the authors explore the usage of RDWT in this specific area of biomedical image application. Redundant wavelet transform (RDWT) has the property that all of the RDWT coefficients locate at the same spatial location as in the original spatial image, which makes it preferable for feature extraction and signal analysis [2]. With the already successful applications of RDWT in image processing and video coding [3,4], the authors built a new system to segment blood vessels using RDWT coefficient mask.Copyright

Explore the multihypothesis motion compensation in video coding

In this paper, different types of mutihypothesis techniques are studied. Based on the transform domain multihypothesis provided in redundant discrete wavelet transform (RDWT), other multihypothesis methods, such as spatial domain or temporal domain multihypothesis are added to improve the performance of a single multihypothesis scheme. Experimental results show that combining two types of multihypothesis motion compensation (MHMC) is promising. Choosing wisely, combining three MHMC methods is possible to get a gain. But as more and more multihypothesis involved, the room of improvement is getting smaller and smaller. At the same time, the increasement of the overhead burden also limits the gain of adding more hypothesis. Also the limitation of combining MHMC techniques along with the vector burden are discussed.