Analysis of Motion in Scale Space

Lunar lander's three-dimensional translation and yaw rotation motion estimation during a descent phase using optical navigation

The aim of this study is to examine the feasibility of the optic flow method in motion of tide flat in the Yellow sea of China. The Landsat TM image is used in construction of optic flow. First,the TM image is registered and corrected. Second, the HS method is applied in optic flow construction. Last, analysis of optic flow results shows that optic flow is a good method for representing motion trend. Generally, this experiment demonstrates that the accuracy of the method is acceptable. It is a promising alternative to describe the change of tide flat topography.

Collection of Solved Nonlinear Problems for Remote Shaping and Patterning of Liquid Structures on Flat and Curved Substrates by Electric and Thermal Fields

This dissertation reports on rate-distortion optimized and computation-constrained video coding algorithms which yield effective and efficient block-based video encoders. We first propose a new cost function for motion estimation which can achieve good tradeoffs among motion vector bit rate, compensation distortion, and number of computations. Based on the new cost function, we propose a predictive motion estimation algorithm which can effectively determine the size of the search region according to the statistics of the motion field. The proposed motion estimation algorithm allows control of the motion vector bit rate and the computational cost, simultaneously. We also develop two efficient rate-distortion optimized coding mode selection algorithms, based on thresholding and finite state machine (FSM) methods, respectively. The thresholding method can eliminate consideration of the computationally expensive modes. The FSM method determines the test orders of the modes and associated parameters by exploiting the local statistics of the input video sequence. The proposed two methods can reduce substantially the computation requirements as compared to the full search mode selection method. Based on the proposed motion estimation and mode selection algorithms, we implement an H.263-based video coder and an MPEG-2, compliant video coder for very low bit rate video applications, and high bit rate interlaced video applications, respectively. The resulting video coders achieve excellent tradeoffs among bit rate, quality, and computational complexity. In fact, experimental results show that our video coders outperform the best known video coders in terms of compression performance and encoding speed.

Tissue motion estimation is an essential step for ultrasound elastography. Our previous study has shown that the affine-model-based optical flow (OF) method outperforms the normalized cross-correlation-based block matching (BM) method in motion estimation. However, the quality of lateral estimation using OF is still low due to inherent limitation of ultrasound imaging. BM-based spatial angular compounding (SAC) has been developed to obtain better motion estimation. In this paper, OF-based SAC (OF-SAC) is proposed to further improve the performance of lateral (and axial) estimation, and it is compared with BM-based SAC (BM-SAC). Plane wave as well as focused wave is transmitted in both simulations and phantom experiments on a linear array. In order to compare the performance quantitatively, the root-mean-square error (RMSE) of axial/lateral displacement and strain, and signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of axial/lateral strain are used as the evaluation criteria in the simulations. In the phantom experiments, the SNR and CNR are used to assess the quality of axial/lateral strain. The results show that for both OF and BM, SAC improves the performance of motion estimation, regardless of using plane or focused wave transmission. More importantly, OF-SAC is shown to outperform BM-SAC with lower RMSE, higher SNR, and higher CNR. In addition, preliminary in vivo experiments on the carotid artery of a healthy human subject also prove the superiority of OF-SAC. These results suggest that OF-SAC is preferred for both axial and lateral motion estimation to BM-SAC.

The growing popularity of high resolution video and the continuously increasing demands for high quality video on mobile devices are producing stronger needs for more efficient video encoder. Concerning these desires, HEVC, a newest video coding standard, has been developed by a joint team formed by ISO/IEO MPEG and ITU/T VCEG. Its design goal is to achieve a 50% compression gain over its predecessor H.264 with an equal or even higher perceptual video quality. Motion Estimation (ME) being as one of the most critical module in video coding contributes almost 50%-70% of computational complexity in the video encoder. This high consumption of the computational resources puts a limit on the performance of encoders, especially for full HD or ultra HD videos, in terms of coding speed, bit-rate and video quality. Thus the major part of this work concentrates on the computational complexity reduction and improvement of timing performance of motion estimation algorithms for HEVC standard. First, a new strategy to calculate the SAD (Sum of Absolute Difference) for motion estimation is designed based on the statistics on property of pixel data of video sequences. This statistics demonstrates the size relationship between the sum of two sets of pixels has a determined connection with the distribution of the size relationship between individual pixels from the two sets. Taking the advantage of this observation, only a small proportion of pixels is necessary to be involved in the SAD calculation. Simulations show that the amount of computations required in the full search algorithm is reduced by about 58% on average and up to 70% in the best case. Secondly, from the scope of parallelization an enhanced TZ search for HEVC is proposed using novel schemes of multiple MVPs (motion vector predictor) and shared MVP. Specifically, resorting to multiple MVPs the initial search process is performed in parallel at multiple search centers, and the ME processing engine for PUs within one CU are parallelized based on the MVP sharing scheme on CU (coding unit) level. Moreover, the SAD module for ME engine is also parallelly implemented for PU size of 32×32. Experiments indicate it achieves an appreciable improvement on the throughput and coding efficiency of the HEVC video encoder. In addition, the other part of this thesis is contributed to the VLSI architecture design for finding the first W maximum/minimum values targeting towards high speed and low hardware cost. The architecture based on the novel bit-wise AND scheme has only half of the area of the best reference solution and its critical path delay is comparable with other implementations. While the FPCG (full parallel comparison grid) architecture, which utilizes the optimized comparator-based structure, achieves 3.6 times faster on average on the speed and even 5.2 times faster at best comparing with the reference architectures. Finally the architecture using the partial sorting strategy reaches a good balance on the timing performance and area, which has a slightly lower or comparable speed with FPCG architecture and a acceptable hardware cost

Motion estimation techniques are widely used in today's video processing systems. The frequently used techniques are frequency-domain motion estimation methods, most notably phase correlation (PC). If the image frames are corrupted by Gaussian noises, then cross-correlation and related techniques do not work well. In this paper, however, we have studied this topic from a viewpoint different from the above. Our scheme is based on the bispectrum method for sub-pixel motion estimation of noisy image sequences. Experimental results show that our proposed method performs significantly better than PC technique.

The new demands for high-definition and high resolution video applications are pushing the development of new techniques in the video coding area. Motion estimation (ME) is one of the key elements in video coding standard which eliminates the temporal redundancies between successive frames. In the recent international video coding standards, sub-pixel ME is proposed for its excellent coding performance. DCT (Discrete Cosine Transform) has been widely used for digital signal processing and multimedia applications, especially video codec. In regards to interpolation for motion estimation and compensation, the conventional HEVC employs 8-tap and 4-tap filters for luma and chroma samples respectively. Coefficients in such filters are determined by DCT. This paper presents and implements the DCT-based Quarter-pixel Interpolation filter for motion estimation and compression of HEVC standard using Matlab.

Document image enhancement is a well investigated field of research. Many approaches based on nonlinear anisotropic diffusion have been proved efficient for removing some common artifacts such as bleed-through. However, the proposed methods are somewhat ineffective in removing bleed-through artifacts while strengthening original side strokes. The purpose of this work is to propose a novel nonlinear anisotropic diffusion approach which enhances foreground edges coherence while smoothly removes background artifacts. The proposed method is based on a structure tensor using a new parameter which permits to better distinguish between foreground and artifacts characters. The diffusion scheme is expressed through a new set of equations using the tensor eigenvalues. This system allows to perform a second discrimination between foreground/background strokes. The performance of the proposed enhancement scheme is evaluated by means of objective measures and perceptual judgment of the obtained results on real images.

Sensor devices are regularly used on unmanned aerial vehicles (UAVs) as reconnaissance and intelligence gathering systems and as support for front line troops on operations. This platform provides a wealth of sensor data and has limited computational power available for processing. The objective of this work is to detect and identify objects in real-time, with a low power footprint so that it can operate on a UAV. An appraisal of current computer vision methods is presented, with reference to their performance and applicability to the objectives. Experimentation with real-time methods of background subtraction and motion estimation was carried out and limitations of each method described. A new, assumption free, data driven method for object detection and identification was developed. The core ideas of the development were based on models that propose that the human vision system analyses edges of objects to detect and separate them and perceives motion separately, a function which has been modelled here by optical flow. The initial development in the temporal domain combined object and motion detection in the analysis process. This approach was found to have limitations. The second iteration used a detection component in the spatial domain that extracts texture patches based on edge contours, their profile, and internal texture structure. Motion perception was performed separately on the texture patches using optical flow. The motion and spatial location of texture patches was used to define physical objects. A clustering method is used on the rich feature set extracted by the detection method to characterise the objects. The results show that the method carries out detection and identification of both moving and static objects, in real-time, irrespective of camera motion.

Nonlinear structure tensors

: The structure of an animals eye is determined by the tasks it must perform. While vertebrates rely on their 2 eyes for all visual functions, insects have evolved a wide range of specialized visual organs to support behaviors such as prey capture, predator evasion, mate pursuit, flight stabilization, and navigation. Compound eyes and ocelli constitute the vision-forming and sensing mechanisms of some flying insects. They provide signals useful for flight stabilization and navigation. In contrast to the well-studied compound eye, the ocelli, seen as the second visual system, sense fast luminance changes and allow for fast visual processing. Using a luminance-based sensor that mimics the insect ocelli and a camera-based motion-detection system, frequency-domain characterization of an ocellar sensor and optic flow (due to rotational motion) is analyzed. Inspired by the insect neurons that make use of signals from both vision-sensing mechanisms, complementary properties of ocellar and optic flow estimates are discussed.

Purpose: A formal analysis and computational examples of the deformation field calculation for optic‐flow‐based image registration algorithms is presented. The addition and composition of the deformation field updates are compared for different types of medium deformation. Method and Materials: A robust family of image registration algorithms is based on the optic flow method. They are iterative and use the conceptual temporal and spatial gradients of the registered images for the determination of the deformation between the objects. This transformation map is obtained iteratively from the current one by: i)the addition and ii)the composition with the update field. These methods are formally different and interplay with image gradients. This effect of the interplay is examined with respect to the type of the deformation. Synthetic and patient images are used in an experiment. Results: The inter‐relation of the deformation field and the gradient forces of the algorithms provides the main gauge of the effectiveness of the iterative process of the determination of the deformation field. The disparity in the alignment of the gradient and the field decreases the efficiency of the iterative process for the additive update. The translational differences between the moving and static image do not affect either methods. The variable deformation is properly addressed by the composition in the iterative process. Conclusion: This analysis can be generalized for any image registration algorithms, which uses the multiple pass approach for the image update in an iterative scheme. The obvious temporal load of the field composition can be mitigated by the use of linear interpolations. For multigrid‐based image registrations, the low resolution steps do can use B‐spline interpolations without sacrificing performance. The improved effectiveness of the deformation field buildup is an important issue for the creation of physically veritable diffeomorphic transformations.

Inspired by recent successes in parallelized optic flow estimation, we propose a variational method which allows to directly estimate dense depth fields from a single hand-held camera in real-time conditions. In particular we show how the central ingredient of the corresponding optic flow method, namely a thresholding scheme, can be generalized to the problem of geometric reconstruction considered in this paper and how it can be parallelized on recent graphics cards. We compare alternative parallelization strategies and experimentally validate that high-quality depth maps can be computed in a few milliseconds from a hand-held camera.

Arterial motion estimation in ultrasound (US) sequences is a hard task due to noise and discontinuities in the signal derived from US artifacts. Characterizing the mechanical properties of the artery is a promising novel imaging technique to diagnose various cardiovascular pathologies and a new way of obtaining relevant clinical information, such as determining the absence of dicrotic peak, estimating the Augmentation Index (AIx), the arterial pressure or the arterial stiffness. One of the advantages of using US imaging is the non-invasive nature of the technique unlike Intra Vascular Ultra Sound (IVUS) or angiography invasive techniques, plus the relative low cost of the US units. In this paper, we propose a semi rigid deformable method based on Soft Bodies dynamics realized by a hybrid motion approach based on cross-correlation and optical flow methods to quantify the elasticity of the artery. We evaluate and compare different techniques (for instance optical flow methods) on which our approach is based. The goal of this comparative study is to identify the best model to be used and the impact of the accuracy of these different stages in the proposed method. To this end, an exhaustive assessment has been conducted in order to decide which model is the most appropriate for registering the variation of the arterial diameter over time. Our experiments involved a total of 1620 evaluations within nine simulated sequences of 84 frames each and the estimation of four error metrics. We conclude that our proposed approach obtains approximately 2.5 times higher accuracy than conventional state-of-the-art techniques.