Retrospection of Nonlinear Adaptive Algorithm-Based Intelligent Plane Image Interaction System

Author:

Guan Zixi1ORCID,Pamba Raja Varma2ORCID,Balachander Bhuvaneswari3ORCID,Khare Deepak Kumar4ORCID,Deb Nabamita5ORCID,Boddu Rajasekhar6ORCID

Affiliation:

1. Shenyang City University, School of Film and Television Media, Liaoning, Shenyang 110112, China

2. LBS Institute of Technology for Women, Poojapura, Thiruvanathapuram, Kerala, India

3. Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India

4. Department of Information Technology, Institute of Engineering and Technology, Dr. Rammanohar Lohiya Avadh University, Ayodhya, UP, India

5. Department of Information Technology, Gauhati University, Assam 781014, India

6. Department of Software Engineering, College of Computing and Informatics, Haramaya University, Dire Dawa, Ethiopia

Abstract

This paper introduces the application and classification of an adaptive filtering algorithm in the image enhancement algorithm. And the filtering noise reduction impact is compared using MATLAB software for programming, image processing, LMS algorithm, RLS algorithm, histogram equalisation algorithm, and Wiener filtering method filtering noise reduction effect. To optimize the intelligent graphic image interaction system, the proposed nonlinear adaptive algorithm of intelligent graphic image interaction system research is based on the digital filter and adaptive filtering algorithm for simulation experiment. The experimental results of several noise index data filtering algorithms show that the fuzzy coefficient k of LMS index is 0.86, RLS index is 0.91, the histogram equalization index is 0.53, and the Wiener filtering index is 0.62. LMS index of quality index Q is 0.90, RLS index is 0.95, histogram equalization index is 0.58, Wiener filtering index is 0.65. According to the above results, comparing LMS with the RLS method and according to SNR, k, and Q values in the simulation results in the process of processing, it is found that the convergence speed of the RLS algorithm is obviously better than that of the LMS algorithm, and the stability is also good. Additionally, the differential imaging data can provide a strong reference for the clinical diagnosis and qualitative differentiation of TBP and CP, and MSCT is worthy of extensive application in the clinical diagnosis of peritonitis. The processing effect of the image with high similarity to the original image is greatly improved compared with the histogram equalization and Wiener filtering methods used in the simulation.

Publisher

Hindawi Limited

Subject

General Mathematics,General Medicine,General Neuroscience,General Computer Science

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