A model based approach to improve the performance of the geometric filtering speckle reduction algorithm

Busse, L.J.; Crimmins, Thomas R.; Fienup, James R.

doi:10.1109/ultsym.1995.495807

Cited by 32 publications

(26 citation statements)

References 4 publications

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“…The output of the analysis is saved in the Matlab workspace for each and every test scenario. Further the output data is plotted for further analyses [16][17][18][19][20]. The pitch-trim setup of SARAS is based on the project specification and requirements.…”

Section: Pitch Trim Mechanical Modelmentioning

confidence: 99%

Optimization of Aircraft Pitch Trim Rate of Movement Using Model Based Approach and Improving the Software Algorithm

Rathinakumar¹,

Nanda²

2015

J Aeronaut Aerospace Eng

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In safety critical systems such as aerospace, it becomes more important since the non-performance of the system as per the requirement may lead to a catastrophe. Also, the work-around to modify the design as per the requirements, generate code, obtain safety clearance from the authorized agency before porting to the target is very time consuming and a cumbersome approach.In this paper, we propose a model-based approach to improve the performance of the software algorithm and optimize the pitch trim movement before porting the code to the target. The effectiveness of the approach is demonstrated with a case study of aerospace domain. The approach encompasses the aircraft sub-system dynamics and the software which operates the sub-system. The analysis of the functionality with performance provides a high level of confidence in the software that is to be ported on to the target. The test crew can provide feedback on the overall functionality and performance of the software at the model-level. The proposed approach not only increases the efficacy of the process but also provides higher safety assurance earlier in the process.Pitch-trim is a critical sub-system of the aircraft which is modeled and the improved software algorithm is incorporated into the model for analyzing the overall functionality and performance of the sub-system. Based on the model simulation and analysis result, the changes in the algorithm were made and finally ported onto the target. The performance and functionality of the pitch-trim sub-system on the aircraft was as per the simulation analysis results indicating the correctness of the model and the proposed approach.

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Section: Pitch Trim Mechanical Modelmentioning

confidence: 99%

Optimization of Aircraft Pitch Trim Rate of Movement Using Model Based Approach and Improving the Software Algorithm

Rathinakumar¹,

Nanda²

2015

J Aeronaut Aerospace Eng

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“…Geometric Filtering [13]: Using a moving, overlapping window of size (3 ⨯ 3), the geometric filter uses an iterative approach to make the center pixel of the window more like its neighboring pixels. The idea behind the geometric filter is that a very small region of an image should be homogeneous.…”

Section: Homogeneous Mask Area Filteringmentioning

confidence: 99%

Ultrasound speckle reduction using coded excitation, frequency compounding, and postprocessing despeckling filters

Ullom¹,

Oelze

Sanchez

2010

2010 IEEE International Ultrasonics Symposium

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Abstract-A technique for improvement of ultrasonic B-mode imaging that uses coded excitation, pulse compression, and frequency compounding was developed. A coded excitation and pulse compression technique known as resolution enhancement compression (REC) was used to enhance the bandwidth of an imaging system by a factor of two. This bandwidth was subdivided into smaller subbands through the speckle-reducing technique known as frequency compounding (REC-FC). Frequency compounded images were generated using various subband widths and then averaged to reduce speckle and to improve contrast while preserving spatial resolution, known as enhanced REC-FC (eREC-FC). In this study, further improvements in contrast and reduction in speckle were obtained by applying post-processing despeckling filters. The following post-processing despeckling filters were explored and analyzed in regard to contrast improvement, speckle reduction, and image feature preservation: median, Lee, homogeneous mask area, geometric, and speckle reducing anisotropic diffusion (SRAD). To quantify the performance of each filter, contrast-to-noise ratio was used. Data from thirty simulated phantoms and experimental data from a tissue-mimicking phantom were generated and filtered. Results demonstrated that post-processing despeckling filters coupled with the eREC-FC technique could improve the image by up to 563%, in terms of the contrast-to-noise ratio, when compared to conventional ultrasonic imaging.

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“…Through iterative repeatition, it tears down the narrow walls (bright edges) and fills up the narrow valleys (dark edges), while smearing and preserving the weak edges. Here we use a 4-directional geometric non-linear noise reduction filter [9]. The filter operates by comparing the intensity of the central pixel (g i,j ) in a 3×3 neighborhood with those of its eight neighbors and modifies its intensity to make it more representative of the surroundings.…”

Section: Geometric Filtering (Gf4d)mentioning

confidence: 99%

Comparative evaluation of speckle reduction algorithms in optical coherence tomography

Pal

Sheet

Chakraborty

et al. 2010

2010 Annual IEEE India Conference (INDICON)

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Speckle is a type of multiplicative noise degrading visual quality in imaging using optical coherence tomography (OCT) resulting in difficulty of assessment by experts. Thus speckle reduction algorithms are required for enhancing image quality of OCT and assisting in their visual assessment. The objective of this work is to evaluate the performance of speckle reduction algorithms using five image quality assessment methods. It presents a comparative evaluation of six speckle reduction filtering techniques based on local statistics, median filtering, pixel homogeneity, geometric filtering, and transformed domain homomorphic filtering. The results of this study suggest that geometric filtering algorithm outperforms other candidate methods, and exhibits minimum mean squared and Minkowski error. Also it has SNR > 50 dB, while having best image quality and intact structural similarity. The experiment performed here for selection of a proper speckle reduction algorithm in OCT requires further large scale evaluation for application in clinical practice, exploratory analysis, automated segmentation, texture analysis, and image based classification techniques. On a wider spectrum this work is also useful as a framework for comparative assessment of similar image quality improvement algorithms.Index Terms-Biomedical image processing, image quality assessment, image restoration, optical tomography, speckle.

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A model based approach to improve the performance of the geometric filtering speckle reduction algorithm

Cited by 32 publications

References 4 publications

Optimization of Aircraft Pitch Trim Rate of Movement Using Model Based Approach and Improving the Software Algorithm

Optimization of Aircraft Pitch Trim Rate of Movement Using Model Based Approach and Improving the Software Algorithm

Ultrasound speckle reduction using coded excitation, frequency compounding, and postprocessing despeckling filters

Comparative evaluation of speckle reduction algorithms in optical coherence tomography

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