Low computational cost improvements of the rate-distortion performance in MPEG-2 rate control

2003 ◽  
Vol 9 (1) ◽  
pp. 41-48
Author(s):  
C Grecos ◽  
J Jiang
Keyword(s):  
Rate Control ◽  
Computational Cost ◽  
Rate Distortion ◽  
Low Computational Cost

scholarly journals A Fast and Efficient Adaptive Threshold Rate Control Scheme for Remote Sensing Images

2012 ◽  
Vol 2012 ◽  
pp. 1-6
Author(s):  
Xiao Chen ◽  
Xiaoqing Xu
Keyword(s):  
Remote Sensing ◽  
Rate Control ◽  
Signal To Noise Ratio ◽  
Computational Cost ◽  
Rate Distortion ◽  
Adaptive Threshold ◽  
Remote Sensing Images ◽  
Minimum Number ◽  
Code Complexity ◽  
Bit Planes

The JPEG2000 image compression standard is ideal for processing remote sensing images. However, its algorithm is complex and it requires large amounts of memory, making it difficult to adapt to the limited transmission and storage resources necessary for remote sensing images. In the present study, an improved rate control algorithm for remote sensing images is proposed. The required coded blocks are sorted downward according to their numbers of bit planes prior to entropy coding. An adaptive threshold computed from the combination of the minimum number of bit planes, along with the minimum rate-distortion slope and the compression ratio, is used to truncate passes of each code block during Tier-1 encoding. This routine avoids the encoding of all code passes and improves the coding efficiency. The simulation results show that the computational cost and working buffer memory size of the proposed algorithm reach only 18.13 and 7.81%, respectively, of the same parameters in the postcompression rate distortion algorithm, while the peak signal-to-noise ratio across the images remains almost the same. The proposed algorithm not only greatly reduces the code complexity and buffer requirements but also maintains the image quality.

FRACTAL BLOCK-MATCHING IN MOTION-COMPENSATED VIDEO CODING

Fractals ◽  
2000 ◽  
Vol 08 (01) ◽  
pp. 35-48 ◽  
Author(s):  
CH. HUFNAGL ◽  
A. UHL
Keyword(s):  
Image Coding ◽  
Computational Cost ◽  
Rate Distortion ◽  
Block Matching ◽  
Video Codecs ◽  
Fractal Image ◽  
Matching Process ◽  
Illumination Changes ◽  
Lower Entropy ◽  
Low Computational Cost

In this work, we propose and investigate techniques developed in the context of fractal image coding for generalizing block-matching algorithms as used in motion-compensated video codecs. By allowing a gray value adaptation (similar to non-iterative fractal techniques) within the block-matching process, we obtain MC error residuals with significantly lower entropy values as compared to pure block-matching. This leads to a significantly improved rate/distortion performance for video sequences with illumination changes or high motion content at a low computational cost.

scholarly journals Computing Expectiles Using k-Nearest Neighbours Approach

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 645
Author(s):  
Muhammad Farooq ◽  
Sehrish Sarfraz ◽  
Christophe Chesneau ◽  
Mahmood Ul Hassan ◽  
Muhammad Ali Raza ◽  
...  
Keyword(s):  
Computational Cost ◽  
Real Life ◽  
Distance Measures ◽  
Computational Time ◽  
High Dimensional ◽  
Test Error ◽  
Nearest Neighbours ◽  
Comparable Performance ◽  
Asymmetric Least Squares ◽  
Low Computational Cost

Expectiles have gained considerable attention in recent years due to wide applications in many areas. In this study, the k-nearest neighbours approach, together with the asymmetric least squares loss function, called ex-kNN, is proposed for computing expectiles. Firstly, the effect of various distance measures on ex-kNN in terms of test error and computational time is evaluated. It is found that Canberra, Lorentzian, and Soergel distance measures lead to minimum test error, whereas Euclidean, Canberra, and Average of (L1,L∞) lead to a low computational cost. Secondly, the performance of ex-kNN is compared with existing packages er-boost and ex-svm for computing expectiles that are based on nine real life examples. Depending on the nature of data, the ex-kNN showed two to 10 times better performance than er-boost and comparable performance with ex-svm regarding test error. Computationally, the ex-kNN is found two to five times faster than ex-svm and much faster than er-boost, particularly, in the case of high dimensional data.

scholarly journals Directional TGV-Based Image Restoration under Poisson Noise

2021 ◽  
Vol 7 (6) ◽  
pp. 99
Author(s):  
Daniela di Serafino ◽  
Germana Landi ◽  
Marco Viola
Keyword(s):  
Computed Tomography ◽  
Image Restoration ◽  
Gaussian Noise ◽  
Computational Cost ◽  
Data Fitting ◽  
Poisson Noise ◽  
Glass Fibres ◽  
Leibler Divergence ◽  
Generalized Variation ◽  
Low Computational Cost

We are interested in the restoration of noisy and blurry images where the texture mainly follows a single direction (i.e., directional images). Problems of this type arise, for example, in microscopy or computed tomography for carbon or glass fibres. In order to deal with these problems, the Directional Total Generalized Variation (DTGV) was developed by Kongskov et al. in 2017 and 2019, in the case of impulse and Gaussian noise. In this article we focus on images corrupted by Poisson noise, extending the DTGV regularization to image restoration models where the data fitting term is the generalized Kullback–Leibler divergence. We also propose a technique for the identification of the main texture direction, which improves upon the techniques used in the aforementioned work about DTGV. We solve the problem by an ADMM algorithm with proven convergence and subproblems that can be solved exactly at a low computational cost. Numerical results on both phantom and real images demonstrate the effectiveness of our approach.

scholarly journals An optimal and low computational cost fractional Newton-type method for solving nonlinear equations

2021 ◽  
pp. 107650
Author(s):  
Giro Candelario ◽  
Alicia Cordero ◽  
Juan R. Torregrosa ◽  
María P. Vassileva
Keyword(s):  
Nonlinear Equations ◽  
Computational Cost ◽  
Type Method ◽  
Low Computational Cost

A Novel Header Bits Estimation Scheme for H.264/AVC Standard

2013 ◽  
Vol 333-335 ◽  
pp. 787-790
Author(s):  
Shu Qian He ◽  
Zheng Jie Deng ◽  
Chun Shi
Keyword(s):  
Rate Control ◽  
Rate Distortion ◽  
Accurate Estimation ◽  
Rate Estimation ◽  
Proposed Model ◽  
Estimation Function ◽  
Estimation Scheme ◽  
Block Based ◽  
Coding Bits ◽  
Distortion Rate

Rate estimation is useful for many H.264/AVC applications including rate-distortion optimization (RDO) for fast mode decision and precise rate control. In this paper, we propose a new header rate prediction model and an adaptive algorithm to provide more accurate estimation of the number of total coding bits for rate control compared to previously proposed methods. The header bit rate estimation is modeled by a linear combination of the number of mode block, and the sum of absolute values of all motion vectors for each block. Based on the proposed model, a header rate estimation function is also proposed to give a more accurate rate-distortion rate control. The proposed schemes can achieve better results in rate-distortion and rate control to previously proposed approaches.

Low-Computational Cost Estimation Algorithm for Adaptive Optics Systems*

2011 ◽  
Vol 44 (1) ◽  
pp. 5573-5578
Author(s):  
M. Abbas Turki ◽  
D. Esqueda Merino ◽  
K. Kasper ◽  
C. Durieu
Keyword(s):  
Adaptive Optics ◽  
Cost Estimation ◽  
Computational Cost ◽  
Estimation Algorithm ◽  
Low Computational Cost

scholarly journals Status Estimation and In-Process Connection of Kanbans Using BLE Beacons and LPWA Network to Implement Intra-Traceability for the Kanban System

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5038
Author(s):  
Kosuke Shima ◽  
Masahiro Yamaguchi ◽  
Takumi Yoshida ◽  
Takanobu Otsuka
Keyword(s):  
Inventory Management ◽  
Low Cost ◽  
Computational Cost ◽  
Low Energy ◽  
Manufacturing Strategy ◽  
Implementation Cost ◽  
Measurement Systems ◽  
Process Route ◽  
Kanban System ◽  
Low Computational Cost

IoT-based measurement systems for manufacturing have been widely implemented. As components that can be implemented at low cost, BLE beacons have been used in several systems developed in previous research. In this work, we focus on the Kanban system, which is a measure used in manufacturing strategy. The Kanban system emphasizes inventory management and is used to produce only required amounts. In the Kanban system, the Kanban cards are rotated through the factory along with the products, and when the products change to a different process route, the Kanban card is removed from the products and the products are assigned to another Kanban. For this reason, a single Kanban cannot trace products from plan to completion. In this work, we propose a system that uses a Bluetooth low energy (BLE) beacon to connect Kanbans in different routes but assigned to the same products. The proposed method estimates the beacon status of whether the Kanban is inside or outside a postbox, which can then be computed by a micro controller at low computational cost. In addition, the system connects the Kanbans using the beacons as paired connection targets. In an experiment, we confirmed that the system connected 70% of the beacons accurately. We also confirmed that the system could connect the Kanbans at a small implementation cost.

scholarly journals Fast Image Registration for Spacecraft Autonomous Navigation Using Natural Landmarks

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Yun-Hua Wu ◽  
Lin-Lin Ge ◽  
Feng Wang ◽  
Bing Hua ◽  
Zhi-Ming Chen ◽  
...  
Keyword(s):  
Image Registration ◽  
Autonomous Navigation ◽  
Computational Cost ◽  
Segmentation Algorithm ◽  
Speeded Up Robust Features ◽  
Speed Up ◽  
Random Sample Consensus ◽  
Invariant Properties ◽  
Low Computational Cost ◽  
Ransac Algorithm

In order to satisfy the real-time requirement of spacecraft autonomous navigation using natural landmarks, a novel algorithm called CSA-SURF (chessboard segmentation algorithm and speeded up robust features) is proposed to improve the speed without loss of repeatability performance of image registration progress. It is a combination of chessboard segmentation algorithm and SURF. Here, SURF is used to extract the features from satellite images because of its scale- and rotation-invariant properties and low computational cost. CSA is based on image segmentation technology, aiming to find representative blocks, which will be allocated to different tasks to speed up the image registration progress. To illustrate the advantages of the proposed algorithm, PCA-SURF, which is the combination of principle component analysis and SURF, is also analyzed in this paper for comparison. Furthermore, random sample consensus (RANSAC) algorithm is applied to eliminate the false matches for further accuracy improvement. The simulation results show that the proposed strategy obtains good results, especially in scaling and rotation variation. Besides, CSA-SURF decreased 50% of the time in extraction and 90% of the time in matching without losing the repeatability performance by comparing with SURF algorithm. The proposed method has been demonstrated as an alternative way for image registration of spacecraft autonomous navigation using natural landmarks.

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