Performance evaluation of a robust fuzzy noise estimation technique in MRI

In underwater environments restricted from human access, many intervention tasks are performed by using robotic systems like underwater manipulators. Commonly, the robotic systems are tele-operated from operating ships; the operation is apt to be inefficient because of restricted underwater information and complex operation methods. In this paper, an assistance technique for tele-manipulation is investigated and evaluated experimentally. The key idea behind the assistance technique is to operate the manipulator by touching several points on the camera images. To implement the idea, the position estimation technique utilizing the touch inputs is investigated. The assistance technique is simple but significantly helpful to increase temporal efficiency of tele-manipulation for underwater tasks. Using URI-T, a cable burying ROV (Remotely Operated Vehicle) developed in Korea, the performance of the proposed assistance technique is verified. The underwater cable gripping task, one of the cable maintenance tasks carried out by the cable burying ROV, is employed for the performance evaluation, and the experimental results are analyzed statistically. The results show that the assistance technique can improve the efficiency of the tele-manipulation considerably in comparison with the conventional tele-operation method.

Download Full-text

Real-time Performance Evaluation of Modified Cascaded Median-based Noise Estimation for Speech Enhancement System

Fluctuation and Noise Letters ◽

10.1142/s0219477519500202 ◽

2019 ◽

Vol 18 (04) ◽

pp. 1950020 ◽

Cited By ~ 1

Author(s):

Bittu Kumar

Keyword(s):

Performance Evaluation ◽

Real Time ◽

Speech Enhancement ◽

Execution Time ◽

Estimation Method ◽

Noise Estimation ◽

Mean Opinion Score ◽

Memory Consumption ◽

Time Performance ◽

Opinion Score

In this paper, the performance evaluation of Modified Cascaded Median (MCM)-based noise estimation method for speech enhancement system has been carried out. The MCM-based method, though reported earlier, was not extensively evaluated; particularly, its real-time performance had not been considered. In the present study, the performance of the MCM-based noise estimation method has been compared with those based on Dynamic Quantile Tracking (DQT) and Cascaded Median (CM), through simulation as well as real-time implementation using TMS320C6416T DSK. All comparisons were made for speech quality (subjectively — mean opinion score and objectively — PESQ score, log-likelihood ratio, weighted spectral slope distance, segmented signal-to-noise ratio and composite measures for signal distortion [Formula: see text], background intrusiveness [Formula: see text] and overall distortion [Formula: see text]) at the 95% level of confidence. The real-time parameters such as memory consumption and execution time have been used for real-time implementation and compared for the three methods. The results, for different SNR-based degraded speech signals, show that the modified cascaded median-based noise estimation is the best in terms of PESQ score, [Formula: see text], [Formula: see text], [Formula: see text] and mean opinion score. On the other hand, for different noise corrupted-based speech signals, it performs well as compared to the original CM. Memory consumption and average execution time for the MCM-based noise estimation lie in-between those for DQT and CM-based methods.

Download Full-text