Down-sampling Filter Research Articles

Research on the Construction Method of 3D Dense Map Based on Visual Slam

Aiming at the problem that visual SLAM (Simultaneous Localization and Mapping) cannot satisfy both high-precision positioning and rapid mapping in large scenes, this paper proposes a map construction method. First, when calculating the pose, the method of combining EPNP and graph optimization is used to optimize the pose estimation to improve the accuracy of the pose. Then, the paper uses Lie algebra to define the vertices and edges of the pose graph, which improves the convergence speed of the model. Finally, when constructing a three-dimensional map, a divide-and-conquer map method is proposed, which uses multiple sub-maps that contain each other for point cloud registration and down-sampling filtering, so as to improve the accuracy of map construction. Experimental results show that the algorithm in this paper has good performance. In the TUM test set, the speed can reach 0. 139s/frame, which is about 0.2s higher than the original method, and the accuracy error RMSE value is reduced to 0.055m. The feasibility of the algorithm is proved, and it can meet the accuracy and speed requirements of 3D dense map construction in large scenes.

Simplification on Cross-Component Linear Model in Versatile Video Coding

To improve coding efficiency by exploiting the local inter-component redundancy between the luma and chroma components, the cross-component linear model (CCLM) is included in the versatile video coding (VVC) standard. In the CCLM mode, linear model parameters are derived from the neighboring luma and chroma samples of the current block. Furthermore, chroma samples are predicted by the reconstructed samples in the collocated luma block with the derived parameters. However, as the CCLM design in the VVC test model (VTM)-6.0 has many conditional branches in its processes to use only available neighboring samples, the CCLM implementation in parallel processing is limited. To address this implementation issue, this paper proposes including the neighboring sample generation as the first process of the CCLM, so as to simplify the succeeding CCLM processes. As unavailable neighboring samples are replaced with the adjacent available samples by the proposed CCLM, the neighboring sample availability checks can be removed. This results in simplified downsampling filter shapes for the luma sample. Therefore, the proposed CCLM can be efficiently implemented by employing parallel processing in both hardware and software implementations, owing to the removal of the neighboring sample availability checks and the simplification of the luma downsampling filters. The experimental results demonstrate that the proposed CCLM reduces the decoding runtime complexity of the CCLM mode, with negligible impact on the Bjøntegaard delta (BD)-rate.

A Study of Image Upsampling and Downsampling Filters

In this paper, a set of techniques used for downsampling and upsampling of 2D images is analyzed on various image datasets. The comparison takes into account a significant number of interpolation kernels, their parameters, and their algebraical form, focusing mostly on linear interpolation methods with symmetric kernels. The most suitable metrics for measuring the performance of upsampling and downsampling filters’ combinations are presented, discussing their strengths and weaknesses. A test benchmark is proposed, and the obtained results are analyzed with respect to the presented metrics, offering explanations about specific filter behaviors in general, or just in certain circumstances. In the end, a set of filters and parameters recommendations is offered based on extensive testing on carefully selected image datasets. The entire research is based on the study of a large set of research papers and on a solid discussion of the underlying signal processing theory.

Enhanced Cross-Component Linear Model for Chroma Intra-Prediction in Video Coding.

Cross-Component Linear Model (CCLM) for chroma intra-prediction is a promising coding tool in Joint Exploration Model (JEM) developed by the Joint Video Exploration Team (JVET). CCLM assumes a linear correlation between the luma and chroma components in a coding block. With this assumption, the chroma components can be predicted by the Linear Model (LM) mode, which utilizes the reconstructed neighbouring samples to derive parameters of a linear model by linear regression. This paper presents three new methods to further improve the coding efficiency of CCLM. First, we introduce a multi-model CCLM (MM-CCLM) approach, which applies more than one linear models to a coding block. With MM-CCLM, reconstructed neighbouring luma and chroma samples of the current block are classified into several groups, and a particular set of linear model parameters is derived for each group. The reconstructed luma samples of the current block are also classified to predict the associated chroma samples with the corresponding linear model. Second, we propose a multi-filter CCLM (MF-CCLM) technique, which allows the encoder to select the optimal down-sampling filter for the luma component with the 4:2:0 colour format. Third, we present a LM-angular prediction (LAP) method, which synthesizes the angular intra-prediction and the MM-CCLM intra-prediction into a new chroma intra coding mode. Simulation results show that 0.55%, 4.66% and 5.08% BD rate savings in average on Y, Cb and Cr components respectively, are achieved for All Intra (AI) configurations with the proposed three methods. MM-CCLM and MF-CCLM have been adopted into the JEM by JVET.

Vision function testing for a suprachoroidal retinal prosthesis: effects of image filtering

Objective. One strategy to improve the effectiveness of prosthetic vision devices is to process incoming images to ensure that key information can be perceived by the user. This paper presents the first comprehensive results of vision function testing for a suprachoroidal retinal prosthetic device utilizing of 20 stimulating electrodes. Further, we investigate whether using image filtering can improve results on a light localization task for implanted participants compared to minimal vision processing. No controlled implanted participant studies have yet investigated whether vision processing methods that are not task-specific can lead to improved results. Approach. Three participants with profound vision loss from retinitis pigmentosa were implanted with a suprachoroidal retinal prosthesis. All three completed multiple trials of a light localization test, and one participant completed multiple trials of acuity tests. The visual representations used were: Lanczos2 (a high quality Nyquist bandlimited downsampling filter); minimal vision processing (MVP); wide view regional averaging filtering (WV); scrambled; and, system off. Main results. Using Lanczos2, all three participants successfully completed a light localization task and obtained a significantly higher percentage of correct responses than using MVP () or with system off (). Further, in a preliminary result using Lanczos2, one participant successfully completed grating acuity and Landolt C tasks, and showed significantly better performance () compared to WV, scrambled and system off on the grating acuity task. Significance. Participants successfully completed vision tasks using a 20 electrode suprachoroidal retinal prosthesis. Vision processing with a Nyquist bandlimited image filter has shown an advantage for a light localization task. This result suggests that this and targeted, more advanced vision processing schemes may become important components of retinal prostheses to enhance performance. ClinicalTrials.gov Identifier: NCT01603576.

ICRS: inter-layer compression method combined with generation of a spatial image pyramid

Currently, generating spatial image pyramid data mainly relies on down-sampling filtration, but so far, there is not any way to evaluate the effect of down-sampling. Herein, down-sampling and up-sampling were combined to form a pair of re-sampling filter, called RSFP, serving as an approximation of the current layer of pyramid data, can be used to evaluate the effect of the down-sampling filter. Based on RSFP, a pyramid-generating approach was built up in here, called it as TDFA. Its filtering depends on the texture direction of the pyramid image data. TDFA down-sampling PSNR was higher than the nearest neighbor interpolation, about 4.51---5.70 dB, while the latter was ever known the best down-sampling filter. The traditional JPEG compression method ignored the close correlations among the pyramid interlayer data, its compression process does not depend on the image texture features, which is not conducive to improving the compression ratio. The proposed RSFP and texture filtering method TDFA can effectively remove both correlations of pyramid image data, which respectively are the inter-layer correlations and its intra-layer texture correlations. Based on the re-sampling filter pair RSFP, combing these two means, an inter-layer compress method ICRS was created in this paper. Under the same reconstruction conditions, ICRS was found to increase the compression ratio 6.02 to 19.70 higher than the conventional AVS's I-frame algorithm, and on the whole, its compression ratio is 3 times or more high than that of JPEG algorithm, and there still is considerable room for improvement.

Design of Lock-In Amplifier Based on Down-Sampling Mean Filter

Low-pass filter is an integral part of lock-in amplifier, low-pass FIR or IIR filter is typically used in lock-in amplifier, which need a large number of multiplications and occupy more hardware resources. To reduce cross-correlation computing requirement of multiplications, this paper, designed orthogonal vector lock-in amplifier based on the down-sampling dual mean filter. Experiments show that, the digital amplifier has good detection performance and noise or clutter suppression. Keywords: lock-in amplifier, mean filter, down-sampling, Gaussian noise suppression, clutter suppression.

Stable discontinuous grid implementation for collocated-grid finite-difference seismic wave modelling

SUMMARY Simulating seismic waves with uniform grid in heterogeneous high-velocity contrast media requires small-grid spacing determined by the global minimal velocity, which leads to huge number of grid points and small time step. To reduce the computational cost, discontinuous grids that use a finer grid at the shallow low-velocity region and a coarser grid at highvelocity regions are needed. In this paper, we present a discontinuous grid implementation for the collocated-grid finite-difference (FD) methods to increase the efficiency of seismic wave modelling. The grid spacing ratio n could be an arbitrary integer n ≥ 2. To downsample the wavefield from the finer grid to the coarser grid, our implementation can simply take the values on the finer grid without employing a downsampling filter for grid spacing ratio n = 2 to achieve stable results for long-time simulation. For grid spacing ratio n ≥ 3, the Gaussian filter should be used as the downsampling filter to get a stable simulation. To interpolate the wavefield from the coarse grid to the finer grid, the trilinear interpolation is used. Combining the efficiency of discontinuous grid with the flexibility of collocated-grid FD method on curvilinear grids, our method can simulate large-scale high-frequency strong ground motion of real earthquake with consideration of surface topography.

Stable discontinuous staggered grid in the finite-difference modelling of seismic motion

SUMMARY We present an algorithm of the spatial discontinuous grid for the 3-D fourth-order velocity–stress staggered-grid finite-difference modelling of seismic wave propagation and earthquake motion. The ratio between the grid spacing of the coarser and finer grids can be an arbitrary odd number. The algorithm allows for large numbers of time levels without inaccuracy and eventual instability due to numerical noise inevitably generated at the contact of two grids with different spatial grid spacings. The key feature of the algorithm is the application of the Lanczos downsampling filter. The algorithm of the discontinuous grid is directly applicable also to the displacement-stress staggered-grid finite-difference scheme.

Reduced area discrete-time down-sampling filter embedded with windowed integration samplers

A technique to implement a discrete-time (DT) sinc3 ↓2 filter for windowed integration samplers is proposed. The topology reduces the idle time of the integration capacitors at the expense of a small complexity overhead in the clock generation, thereby saving 33% of the die area compared to the currently existing topology. Circuit level simulations in 45 nm CMOS technlogy shows good agreement with the predicted behaviour obtained from the analaysis.

Compression of Laplacian Pyramids Through Orthogonal Transforms and Improved Prediction

Scalable representation of visual signals, such as image and video signals, has become a subject of active research since early 1980s. Scalability allows the adaptation of the bit rate and/or the resolution of the transmitted data to the network bandwidth and/or the rendering capability of the receiving device. For many years, spatial scalability has been achieved through wavelets, but recently the Laplacian pyramid (LP) has become an alternative choice because of reduced aliasing in the lower resolutions. In this paper, we focus on the coding efficiency of the LP with a view to transmitting it over a communication channel. In particular, we aim to improve the compression efficiency of the LP detail layers through improved interlayer prediction and orthogonal spatial transforms. First, we consider an LP in the open-loop configuration and propose to improve its rate-distortion performance by compressing it to a critically sampled representation. We derive four different orthogonal spatial transforms from the upsampling and downsampling filters that can achieve this representation, and apply them on the detail layers. The application of these transforms to the detail layers renders a fixed number of transform coefficients either zero or redundant, thus making their transmission unnecessary. Then we consider the compression of an LP in the closed-loop configuration through similar spatial transforms. Because of the introduction of quantization in the prediction loop, these spatial transforms applied on the detail layers do not produce the same number of zero or redundant transform coefficients as in the open-loop case. Nevertheless, the insight obtained from the open-loop coding leads us to enhance the interlayer prediction, and the subsequent application of the spatial transforms to the new detail layers aims to achieve better energy compaction.

Influence of downsampling filter characteristics on compression performance in wavelet-based scalable video coding

The application of different downsampling filters in video coding directly models visual information at lower resolutions and influences the compression performance of a chosen coding system. In wavelet-based scalable video coding the spatial scalability is achieved by the application of wavelets as downsampling filters. However, characteristics of different wavelets influence the performance at targeting spatio-temporal decoding points. An analysis of different downsampling filters in popular wavelet-based scalable video coding schemes is presented. Evaluation is performed for both intra- and inter-coding schemes using wavelets and standard downsampling strategies. On the basis of the obtained results a new concept of inter-resolution prediction is proposed, which maximises the average performance using a combination of standard downsampling filters and wavelet-based coding.

Scalable Video Coding with Interlayer Signal Decorrelation Techniques

Scalability is one of the essential requirements in the compression of visual data for present-day multimedia communications and storage. The basic building block for providing the spatial scalability in the scalable video coding (SVC) standard is the well-known Laplacian pyramid (LP). An LP achieves the multiscale representation of the video as a base-layer signal at lower resolution together with several enhancement-layer signals at successive higher resolutions. In this paper, we propose to improve the coding performance of the enhancement layers through efficient interlayer decorrelation techniques. We first show that, with nonbiorthogonal upsampling and downsampling filters, the base layer and the enhancement layers are correlated. We investigate two structures to reduce this correlation. The first structure updates the base-layer signal by subtracting from it the low-frequency component of the enhancement layer signal. The second structure modifies the prediction in order that the low-frequency component in the new enhancement layer is diminished. The second structure is integrated in the JSVM 4.0 codec with suitable modifications in the prediction modes. Experimental results with some standard test sequences demonstrate coding gains up to 1 dB for I pictures and up to 0.7 dB for both I and P pictures.

Image downsampling for interlaced- to-progressive transcoding in discrete cosine transform domain

We propose a new image-downsampling method for interlaced-to-progressive transcoding. The proposed image-downsampling method is performed in the discrete cosine transform (DCT) domain. We develop a downsampling filter matrix that transcodes the interlaced picture into the progressive picture. The method shows a good peak signal-to-noise ratio (PSNR) compared with spatial-domain downsampling.

Wavelet-Based Multiresolution with

Multiresolution methods are a common technique used for dealing with large-scale data and representing it at multiple levels of detail. We present a multiresolution hierarchy construction based on n√2 subdivision, which has all the advantages of a regular data organization scheme while reducing the drawback of coarse granularity. The n√2-subdivision scheme only doubles the number of vertices in each subdivision step regardless of dimension n. We describe the construction of 2D, 3D, and 4D hierarchies representing surfaces, volume data, and time-varying volume data, respectively. The 4D approach supports spatial and temporal scalability. For high-quality data approximation on each level of detail, we use downsampling filters based on n-variate B-spline wavelets. We present a B-spline wavelet lifting scheme for n√2-subdivision steps to obtain small or narrow filters. Narrow filters support adaptive refinement and out-of-core data exploration techniques.

Fast motion vector re-estimation for transcoding MPEG-1 into MPEG-4 with lower spatial resolution in DCT-domain

In this paper, we propose a fast motion vector re-estimation for transcoding MPEG-1 to MPEG-4 with lower spatial resolution. This task can be performed in the pixel-domain or in the discrete cosine transform (DCT) domain. In this paper, we concentrate on the DCT-domain approach, which requires lower delay and complexity than those in the pixel-domain. For the DCT-domain transcoding to lower spatial resolution pictures, DCT-domain down-sampling filter is applied and a base motion vector (BMV) for the down-sampled MPEG-4 macroblock is to be calculated from the input motion vectors operating on the higher spatial resolution image. Quality can be significantly improved by refining the BMV. Starting with the BMV, the motion vector refinement (MVR) scheme searches for a delta motion vector within a significantly reduced search area. We propose a fast MVR scheme for video down-sampling in the DCT-domain based on minimizing the number of required check points, and a computationally efficient method for extracting motion compensated DCT block. We also show an efficient scheme for selecting a coding mode for a macroblock in the lower resolution video from those of the corresponding higher resolution video.

Investigations into Reduced-Resolution Optical Correlators with Realistic Spatial Light Modulator Fill Factors

The design of reduced-resolution filters by multiresolution analysis (MA) or by downsampling is extended to spatial light modulators with fill factors less than one. Analysis shows that the dependence of the zero-order correlation peaks with fill factor varies with target size for both design techniques. Also, a practicable performance improvement is obtained for MA compared with downsampling for small- to medium-sized targets that is greater for larger fill factors. The validity of the analysis is confirmed by simulation. A reduced-resolution optical correlator is constructed, and a comparison of MA and downsampling filters is performed for different-sized targets. The experimental results show good qualitative agreement with the simulation; however, the first-order correlation peaks were found to be greater for the experimental results. A possible reason for this is that the manufacturer's fill-factor specification might be too large; therefore a new technique for measuring the fill factor is proposed.