Jiali Li

Bio: Jiali Li is an academic researcher from Hong Kong University of Science and Technology. The author has contributed to research in topics: Pixel & Motion estimation. The author has an hindex of 7, co-authored 22 publications receiving 133 citations. Previous affiliations of Jiali Li include University of Hong Kong.

Novel RD-Optimized VBSME With Matching Highly Data Re-Usable Hardware Architecture

Abstract: To achieve superior performance, rate-distortion optimized motion estimation (ME) for variable block size (RDO VBSME) is often used in state-of-the-art video coding systems such as the H.264 JM software. However, the complexity of RDO-VBSME is very high both for software and hardware implementations. In this paper, we propose a hardware-friendly ME algorithm called RDOMFS with a novel hardware-friendly rate-distortion (RD)-like cost function, and a hardware-friendly modified motion vector predictor. Simulation results suggest that the proposed RDOMFS can achieve essentially the same RD performance as RDO-VBSME in JM. We also propose a matching hardware architecture with a novel Smart Snake Scanning order which can achieve very high data re-use ratio and data throughout. It is also reconfigurable because it can achieve variable data re-use ratio and can process variable frame size. The design is implemented with TSMC 0.18 μm CMOS technology and costs 103 k gates. At a clock frequency of 63 MHz, the architecture achieves real-time 1920 × 1080 RDO-VBSME at 30 frames/s. At a maximum clock frequency of 250 MHz, it can process 4096 × 2160 at 30 frames/s.

Multichannel Nonlocal Means Fusion for Color Image Denoising

Abstract: In this paper, we propose an advanced color image denoising scheme called multichannel nonlocal means fusion (MNLF), where noise reduction is formulated as the minimization of a penalty function. An inherent feature of color images is the strong interchannel correlation, which is introduced into the penalty function as additional prior constraints to expect a better performance. The optimal solution of the minimization problem is derived, consisting of constructing and fusing multiple nonlocal means (NLM) spanning all three channels. The weights in the fusion are optimized to minimize the overall mean squared denoising error, with the help of the extended and adapted Stein's unbiased risk estimator (SURE). Simulations on representative test images under various noise levels verify the improvement brought by the multichannel NLM, compared to the traditional single-channel NLM. In the meantime, MNLF provides competitive performance both in terms of the color peak signal-to-noise ratio and in perceptual quality when compared with other state-of-the-art benchmarks.

Improved combined inter-intra prediction using spatial-variant weighted coefficient

Abstract: In current video coding standard H.264/AVC, pixel prediction is applied to reduce spatial and temporal redundancy existed in video signal. Previously, it has been shown that better coding performance is achieved compared to H.264/AVC by combining inter and intra prediction to generate a more accurate prediction. In this paper, an improved combined prediction scheme is presented which allows the video codec to tune weighted coefficient for inter prediction and intra prediction adaptively to local signal characteristics. In order to avoid additional overhead signalling, statistics of already coded neighboring block is analyzed to predict the weighted coefficients of the combined prediction for current macroblock. Compared to H.264/AVC, coding performance is increased by up to 1.9%. And compared to the latest combined prediction method using spatial-invariant weighted coefficients, simulation results show that the proposed scheme achieves additional coding gain of up to 0.66%.

Stereo Matching with Optimal Local Adaptive Radiometric Compensation

Abstract: A common assumption in stereo matching is that the corresponding pixels in stereo images have similar pixel values. Unfortunately, such an assumption may not be true due to radio- metric variations in different views, leading to severely degraded matching results. In this letter, we propose a radiometrically in- variant stereo matching algorithm called Optimal Local Adaptive Radiometric Compensation (LARAC) .I nLARAC, we approximate the spatially varying Pixel Value Correspondence Function (PVCF) between a corresponding pixel pair as a locally consistent polyno- mial within an optimal local adaptive window. The optimal poly- nomial coefficients are obtained for each candidate disparity value and are used to compute the matching cost. Meanwhile, a self-cor- rection property is achieved by the proposed LARAC ,l eading to reduced matching errors for the outlier pixels. Experimental re- sults suggest that the proposedLARACoutperforms other state-of- the-art stereo matching algorithms.

Hybrid plane fitting for depth estimation

Abstract: In this paper, a novel plane fitting algorithm with low complexity and high accuracy is proposed to refine the depth maps generated by stereo matching We first compute the confidence coefficient for each pixel in the depth map by cross checking and stable pixel calculation According to the outlier pixel percentage for each segment, we choose one method, either proposed weighted least square error based or RANSAC based plane fitting algorithm, to estimate the plane parameters Experimental results show that our method outperforms other existing plane fitting algorithms

Radiometry and the Detection of Optical Radiation

Abstract: Microwave Radiometric Detection of Oil SlicksRadiometry and the Detection of Optical RadiationOptical Systems Design Detection EssentialsOptoelectronic Workshops 7: Advanced Technology for Radiometry and the Detection of Optical RadiationStudies of Radio Frequency Interference Detection Methods in Microwave RadiometryPassive Infrared DetectionAdvances in Radiometry ResearchDetection and Assessment of Dental CariesMicrowave and Millimeterwave Remote Sensing for Security ApplicationsNon-Imaging Microwave and Millimetre-Wave Sensors for Concealed Object DetectionIntroduction to Radiometry and Photometry, Second EditionOptical Radiation Measurements: Grum, F. C., Becherer, R. RadiometryMicrowave Radiometric Studies in Relation to Mine DetectionMicrowave Radiometry and Remote Sensing of the Earth's Surface and AtmosphereMILLIMETER WAVE RADIOMETRIC DETECTION OF TARGETS OBSCURED BY FOLIAGE.Applied Photometry, Radiometry, and Measurements of Optical LossesPassive Standoff Detection of Chemical Vapors by Differential FTIR RadiometryClinical Application of Microwave Radiometry Techniques in the Detection of CancerPhotometry, Radiometry, and Measurements of Optical LossesRadiometryIce/frost Detection Using Millimeter Wave RadiometryFeasibility Study of Radiometry for Airborne Detection of Aviation HazardsEM Detection of Concealed TargetsLaser Photothermal Radiometry for the Detection of Early Enamel DemineralizationRadio Frequency Radiometry for the Remote Airborne Detection of Small Forest FirDetection and Characterization of Nuclear CloudsAn Application of Pattern Recognition to Radiometric Target DetectionTheory of Broadband Autocorrrelation Radiometry for Spectral Line DetectionInfrared Detectors and SystemsRadiometry Detection of Acoustic SignalsDetection of Greenbug Infestation Using Ground-based RadiometryRadiometry and the Detection of Optical RadiationW-band Radiometry for the Non-invasive Investigation of MaterialsHuman Presence Detection Using Millimeter-wave RadiometryRadiometry for Low Target DetectionUse of Airborne Microwave Radiometry for the Detection and Investigation of Oil Slicks at SeaFeasibility Study of Radiometry for Airborne Detection of Aviation HazardsIntroduction to Radiometry and PhotometryRadio Frequency Interference Characterization and Detection in L-band Microwave RadiometryDetection of Abandoned Underground Coal Mines by Geophysical Methods

Literature Survey on Stereo Vision Disparity Map Algorithms

Abstract: This paper presents a literature survey on existing disparity map algorithms. It focuses on four main stages of processing as proposed by Scharstein and Szeliski in a taxonomy and evaluation of dense two-frame stereo correspondence algorithms performed in 2002. To assist future researchers in developing their own stereo matching algorithms, a summary of the existing algorithms developed for every stage of processing is also provided. The survey also notes the implementation of previous software-based and hardware-based algorithms. Generally, the main processing module for a software-based implementation uses only a central processing unit. By contrast, a hardware-based implementation requires one or more additional processors for its processing module, such as graphical processing unit or a field programmable gate array. This literature survey also presents a method of qualitative measurement that is widely used by researchers in the area of stereo vision disparity mappings.

Introduction to the special issue on multimedia implementation », IEEE Trans. On Circuits and Systems for Video Technology

Abstract: Keywords: LTS3 Reference LTS-ARTICLE-2004-019 Record created on 2006-06-14, modified on 2016-08-08

Image Restoration Using Joint Statistical Modeling in a Space-Transform Domain

Abstract: This paper presents a novel strategy for high-fidelity image restoration by characterizing both local smoothness and nonlocal self-similarity of natural images in a unified statistical manner. The main contributions are three-fold. First, from the perspective of image statistics, a joint statistical modeling (JSM) in an adaptive hybrid space-transform domain is established, which offers a powerful mechanism of combining local smoothness and nonlocal self-similarity simultaneously to ensure a more reliable and robust estimation. Second, a new form of minimization functional for solving the image inverse problem is formulated using JSM under a regularization-based framework. Finally, in order to make JSM tractable and robust, a new Split Bregman-based algorithm is developed to efficiently solve the above severely underdetermined inverse problem associated with theoretical proof of convergence. Extensive experiments on image inpainting, image deblurring, and mixed Gaussian plus salt-and-pepper noise removal applications verify the effectiveness of the proposed algorithm.