Robust Radiometric Normalization of the near Equatorial Satellite Images Using Feature Extraction and Remote Sensing Analysis

Relative radiometric normalization (RRN) minimizes radiometric differences among images caused by inconsistencies of acquisition conditions rather than changes in surface. Scale invariant feature transform (SIFT) has the ability to automatically extract control points (CPs) and is commonly used for remote sensing images. However, its results are mostly inaccurate and sometimes contain incorrect matching caused by generating a small number of false CP pairs. These CP pairs have high false alarm matching. This paper presents a modified method to improve the performance of SIFT CPs matching by applying sum of absolute difference (SAD) in a different manner for the new optical satellite generation called near-equatorial orbit satellite and multi-sensor images. The proposed method, which has a significantly high rate of correct matches, improves CP matching. The data in this study were obtained from the RazakSAT satellite a new near equatorial satellite system. The proposed method involves six steps: 1) data reduction, 2) applying the SIFT to automatically extract CPs, 3) refining CPs matching by using SAD algorithm with empirical threshold, and 4) calculation of true CPs intensity values over all image’ bands, 5) preforming a linear regression model between the intensity values of CPs locate in reverence and sensed image’ bands, 6) Relative radiometric normalization conducting using regression transformation functions. Different thresholds have experimentally tested and used in conducting this study (50 and 70), by followed the proposed method, and it removed the false extracted SIFT CPs to be from 775, 1125, 883, 804, 883 and 681 false pairs to 342, 424, 547, 706, 547, and 469 corrected and matched pairs, respectively.

A detail-preserving random-valued impulse noise removal algorithm based on S-ROAD

In a random-valued impulse noise corrupted image, in order to remove impulse noise and, meanwhile, efficiently preserve image edges and details, a novel two-phase detail- preserving random-valued impulse noise removal algorithm is proposed. At the noise detecting phase, an image statistic called S-estimate based rank-ordered absolute difference （S- ROAD） is presented to distinguish image edge and detail pixels from impulse noise pixels in a noise corrupted image. By introducing S-estimate into ROAD statistic, the interference caused by the image edges and details in the ROAD statistic is eliminated. With the S-ROAD statistic, most of the noise pixels, including the noise at edges and details, can be distinguished. At the noise pixels filtering phase, a two-threshold iterative method is used to restore the identified noise pixels and the estimate precision is improved; thus, the image details can be efficiently preserved. Experimental results show that the proposed method provides a significant improvement over many existing filters in terms of both subjective and objective evaluations.

Improved block matching approach to fast disparity estimation

An improved block matching approach to fast disparity estimation in machine vision applications is proposed, where the matching criterion is the sum of the absolute difference（SAD）.By evaluating the lower bounds, which become increasingly tighter for the matching criteria, the method tries to successively terminate unnecessary computations of the matching criteria between the reference block in one image and the ineligible candidate blocks in another image.It also eliminates the ineligible blocks as early as possible, while ensuring the optimal disparity of each pixel.Also, the proposed method can further speed up the elimination of ineligible candidate blocks by efficiently using the continuous constraint of disparity to predict the initial disparity of each pixel.The performance of the new algorithm is evaluated by carrying out a theoretical analysis, and by comparing its performance with the disparity estimation method based on the standard block matching.Simulated results demonstrate that the proposed algorithm achieves a computational cost reduction of over 50.5% in comparision with the standard block matching method.

Real-time digital image stabilization based on regional field image gray projection

Digital image stabilization technique plays important roles in video surveillance and object acquisition.Many useful electronic image stabilization algorithms have been studied.A real-time algorithm is proposed based on field image gray projection which enables the regional odd and even field image to be projected into x and y directions and thus to get the regional gray projection curves in x and y directions,respectively.For the odd field image channel,motion parameters can be estimated via iterative minimum absolute difference based on two successive field image regional gray projection curves.Then motion compensations can be obtained after using the Kalman filter method.Finally,the odd field image is adjusted according to the compensations.In the mean time,motion compensation is applied to the even field image channel with the odd field image gray projection curves of the current frame.By minimizing absolute difference between odd and even field image gray projection curves of the current frame,the inter-field motion parameters can be estimated.Therefore,the even field image can be adjusted by combining the inter-field motion parameters and the odd field compensations.Finally,the stabilized image sequence can be obtained by synthesizing the adjusted odd and even field images.Experimental results show that the proposed algorithm can run in real-time and have a good stabilization performance.In addition,image blurring can be improved.

Automatic Fast and Robust Technique to Refine Extracted SIFT Key Points for Remote Sensing Images

The scale-invariant feature transform(SIFT)ability to automatic control points(CPs)extraction is very well known on remote sensing images,however,its result inaccurate and sometimes has incorrect matching from generating a small number of false CPs pairs,their matching has high false alarm.This paper presents a method containing a modification to improve the performance of the SIFT CPs matching by applying sum of absolute difference(SAD)in different manner for the new optical satellite generation called near-equatorial orbit satellite(NEqO)and multi-sensor images.The proposed method leads to improving CPs matching with a significantly higher rate of correct matches.The data in this study were obtained from the RazakSAT satellite covering the Kuala Lumpur-Pekan area.The proposed method consists of three parts:(1)applying the SIFT to extract CPs automatically,(2)refining CPs matching by SAD algorithm with empirical threshold,and(3)evaluating the refined CPs scenario by comparing the result of the original SIFT with that of the proposed method.The result indicates an accurate and precise performance of the model,which showed the effectiveness and robustness of the proposed approach.

ALL ZERO MACROBLOCK DECISION METHOD FOR H.26L

In order to reduce the computation in the part of motion search and transform in H.26L encoder, an all-zero macroblock decision method based on integer transform and motion search is proposed in this paper. According to the characteristics of integer transform and motion search in H.26L, all-zero macroblock decision is made in inter frame coding by comparing Sum of the Absolute Differences(SAD) with a value related with Quantization Parameter(QP)before integer transform. It avoids a large amount of computation in motion search, transform and quantization. This technology highly improves the efficiency of real time H.26L encoder by skipping all-zero macroblock before integer transform and shortening the code stream at the same time.

An Improved Rate Control Method Based on Modification at Scene Change for H.264

This paper presents an improved rate control method for H.264. First, the scene changes are detected by the average absolute difference of the brightness histograms between the adjacent frames. Then, the bit allocation and quantization parameters are adjusted, using a certain threshold. In addition, the calculation of the mean absolute difference （MAD） is modified in an alternative way, which makes the rate distortion optimization （RDO） more accurate. Extensive simulation results show that the proposed method, compared with G012, can improve the average peak signal-to-noise ratio （PSNR） and moderate the image quality.

Reduced bit low power VLSI architectures for motion estimation

Low power and real time very large scale integration （VLSI） architectures of motion estimation （ME） algorithms for mobile devices and applications are presented. The power reduction is achieved by devising a novel correction recovery mechanism based on algorithms which allow the use of reduced bit sum of absolute difference （RBSAD） metric for calculating matching error and conversion to full resolution sum of absolute difference （SAD） metric whenever necessary. Parallel and pipelined architectures for high throughput of full search ME corresponding to both the full resolution SAD and the generalized RBSAD algorithm are synthe- sized using Xilinx Synthesis Tools （XST）, where the ME designs based on reduced bit （RB） algorithms demonstrate the reduction in power consumption up to 45% and/or the reduction in area up to 38%.

A Simple Adaptive Rate Control for H.264/AVC

The purpose of this paper is to improve allocation of the number of bits without skipping the frame by accurately estimating the target bits in H.264/AVC rate control.In our scheme,we propose an enhancement method of the target frame rate based H.264/AVC bit allocation.The enhancement uses a frame complexity estimation to improve the existing mean absolute difference(MAD)complexity measurement Bit allocation to each frame is not just computed by target frame rate but also adjusted by a combined frame complexity measure.Using the statistical characteristic,we obtain change of occurrence bit about QP to apply the bit amount by QP from the video characteristic and applied in the estimated bit amount of the current frame. Simulation results show that the proposed rate control scheme could not only achieves time saving of more than 99%over existing rate control algorithm,but also increase the average PSNR of reconstructed video for around 0.02～0.78 dB in all the sequences.

Adaptive Rate Control Scheme for H.264/AVC

The purpose of this paper is to improve allocation of the number of bits without skipping the frame by accurately estimating the target bits in H. 264/AVC rate control. The scheme ImPoses an enhancement method of the target frame rate based on H. 264/AVC bit allocation. The enhancement uses a frame complexion estimation to improve the existing Mean Absolute Difference （MAD） complexity measurement. Bit allocation to each frame is not just computed by target frame rote but also adjusted by a combined frame complexity measure. Using the statistical characteristic, the scheme obtains change of occurrence bit about QP to apply the bit amount by QP from the video characteristic and apply it in the estimated bit amount of the current frame. Simulation results show that the proposed rate eontrol scheme achieves time saving of mine than 99% over existing rate control algorithm. Nevertheless, Peak Signal-to-Noise Ration （PSNR） and bit rate were almost the same as the performances.

Geometric Correction Analysis of Highly Distortion of Near Equatorial Satellite Images Using Remote Sensing and Digital Image Processing Techniques

The Near-equatorial orbit (NEqO) satellite represents a new generation of optical satellite images characterized by nonlinear distortion when captured. Conventional modeling techniques are insufficient to overcome the geometric distortion in these satellite images. This study proposes a new methodology for overcoming the geometric distortion of the NEqO images. The data used are obtained from RazakSAT and SPOT-5 satellite images in Malaysia. The method starts with applying the RI-SIFT algorithm to extract control points (CPs) automatically. These CPs are used to solve for the transformation parameters of the geometric correction model by applying spline transformations. The result is verified through statistical comparison: 1) geometric correction on the RazakSAT image is performed with Spot satellite image with using first-order polynomial trans-formation. 2) Then calculate the root mean square error (RMSE). 3) Compare the calculated RMSE with that obtained from the first step with that of the proposed method. The RMSE value of the geometric corrections using the proposed method was 7.08 × 10−9 m. The proposed method provides promising results.

Performance of Dexcom G5 and FreeStyle Libre sensors tested simultaneously in people with type 1 or 2 diabetes and advanced chronic kidney disease

BACKGROUND Advanced chronic kidney disease(CKD) is a common complication for people with type 1 and 2 diabetes and can often lead to glucose instability. Continuous glucose monitoring(CGM) helps users monitor and stabilize their glucose levels. To date, CGM and intermittent scanning CGM are only approved for people with diabetes but not for those with advanced CKD.AIM To compare the performance of Dexcom G5 and FreeStyle Libre sensors in adults with type 1 or 2 diabetes and advanced CKD.METHODS This was a non-randomized clinical trial that took place in two outpatient clinics in western Sweden. All patients with type 1 or 2 diabetes and an estimated glomerular filtration rate(eGFR) of < 30 mL/min per 1.73 m^(2) were invited to participate. Forty patients(full analysis set = 33) carried the Dexcom G5 sensor for 7 d and FreeStyle Libre sensor for 14 d simultaneously. For referencing capillary blood glucose(SMBG) was measured with a high accuracy glucose meter(HemoCue®) during the study period. At the end of the study, all patients were asked to answer a questionnaire on their experience using the sensors.RESULTS The mean age was 64.1(range 41-77) years, hemoglobin A1 c was 7.0% [standard deviation(SD) 3.2], and diabetes duration was 28.5(SD 14.7) years. A total of 27.5% of the study population was on hemodialysis and 22.5% on peritoneal dialysis. The mean absolute relative difference for Dexcom G5 vs SMBG was significantly lower than that for FreeStyle Libre vs SMBG [15.2%(SD 12.2) vs 20.9%(SD 8.6)], with a mean difference of 5.72 [95% confidence interval(CI): 2.11-9.32;P = 0.0036]. The mean absolute difference was also significantly lower for Dexcom G5 than for FreeStyle Libre, 1.21 mmol/L(SD 0.78) and 1.76 mmol/L(SD 0.78), with a mean diffrenec of 0.55(95%CI: 0.27-0.83;P = 0.0004).The mean difference(MD) was-0.107 mmol/L and-1.10 mmol/L(P = 0.0002), respectively. In all, 66% of FreeStyle Libre values were in the no risk zone on the surveillance error grid compared to 82% of Dexcom G5 values.CONCLUSION Dexcom G5 produces more accurate sensor values than FreeStyle Libre in people with diabetes and advanced CKD and is likely safe to be used by those with advanced CKD.

Inter-comparison of Raingauges on Rainfall Amount and Intensity Measurements in a Tropical Environment

The HKO （Hong Kong Observatory） has been carrying out an inter-comparison of automatic raingauges since 2011 for identifying raingauges that can meet the ~ 5% accuracy requirement of the WMO （World Meteorological Organization） in measuring rainfall amount. The inter-comparison was conducted at HKO＇s meteorological stations at King＇s Park and Hong Kong International Airport in Hong Kong. Two 0.1-mm resolution Pluvio-OTT weighing gauges were introduced in 2013. This type of raingauges has outperformed others in the WMO＇s field inter-comparison held between October 2007 and April 2009. The performances of 14 raingauges, comprising five different measurement methods, viz. drop-counting, weighing, tipping bucket with software correction, tipping bucket with extra pulse correction and tipping bucket without correction, were evaluated. The focus was to study their performances in rainfall intensity measurement, especially during heavy rain situations. Different high rainfall intensity episodes were selected for analysis. Among these episodes, the maximum 1-minute rainfall intensity as high as around 130 mm/hr was recorded by the Pluvio-OTT raingauges. This paper serves to conclude the 3-year （2011-2013） inter-comparison exercise for rainfall amount measurements and to provide preliminary 1-year （2013） comparison results on rainfall intensity measurements.

An adaptive fast search algorithm for block motion estimation in H.264

Motion estimation is an important issue in H.264 video coding systems because it occupies a large amount of encoding time.In this paper,a novel search algorithm which utilizes an adaptive hexagon and small diamond search (AHSDS) is proposed to enhance search speed.The search pattern is chosen according to the motion strength of the current block.When the block is in active motion,the hexagon search provides an efficient search means;when the block is inactive,the small diamond search is adopted.Simulation results showed that our approach can speed up the search process with little effect on distortion performance compared with other adaptive approaches.

Consistent Depth Maps Estimation from Binocular Stereo Video Sequence

In the paper, an approach is proposed for the problem of consistency in depth maps estimation from binocular stereo video sequence. The consistent method includes temporal consistency and spatial consistency to eliminate the flickering artifacts and smooth inaccuracy in depth recovery. So the improved global stereo matching based on graph cut and energy optimization is implemented. In temporal domain, the penalty function with coherence factor is introduced for temporal consistency, and the factor is determined by Lucas-Kanade optical flow weighted histogram similarity constraint(LKWHSC). In spatial domain, the joint bilateral truncated absolute difference(JBTAD) is proposed for segmentation smoothing. The method can smooth naturally and uniformly in low-gradient region and avoid over-smoothing as well as keep edge sharpness in high-gradient discontinuities to realize spatial consistency. The experimental results show that the algorithm can obtain better spatial and temporal consistent depth maps compared with the existing algorithms.