The usage of a fused image and compressed model in a VLSI implementation is demonstrated. In this study, distortion correction is also considered. In distortion correction models, least-squares estimate is utilized. The technique of picture fusion is widely employed in medical imaging. Many pictures are obtained from various sensors (or) multiple images are captured at different times by one sensor in the image fusion approach. CT scans give useful information on denser tissue with the least amount of distortion. The information obtained from a magnetic resonance imaging (MRI) of soft tissue with significant distortion is useful. The DWT-based image fusion approach employs discrete wavelet transforms, a novel multi-resolution analytic tool. Back mapping expansion polynomial is used to reduce computer complexity. Using 0.18um technology, the suggested VLSI design achieves 218MHz with 1480 logical components.

Keywords: Distortion correction, DWT, Image fusion, Horner’s Algorithm, Back mapping.

[1] M. Mohankumar, V. Gopalakrishnan and S.Yasotha, (2015). A VLSI Approach for Distortion Correction in Surveillance Camera Images. ARPN Journal of Engineering and Applied Sciences, 10(9): 4105-4108.

[2] Yang, L., Wang, Y., Wang, Z. et al. (2020). A new method based on stacked auto-encoders to identify abnormal weather radar echo images. J Wireless Com Network 2020, 177.

[3] M.Mohankumar, R.Gowrimanohari, (2015). VLSI Architecture for Barrel Distortion Correction In Surveillance Camera Images. Journal of Electronics and Computer Science, 2(5).

[4] Hareeta, M., Mahendra, K., Anurag, P. (2016). Image Fusion Based on the Modified Curvelet Transform. In: Unal, A., Nayak, M., Mishra, D.K., Singh, D., Joshi, A. (eds) Smart Trends in Information Technology and Computer Communications. SmartCom 2016. Communications in Computer and Information Science, vol 628. Springer, Singapore.

[5] Al-Azzawi, N.A. (2018). Color Medical Imaging Fusion Based on Principle Component Analysis and F-Transform. Pattern Recognit. Image Anal. 28: 393-399.

[6] Wang, Hh. (2004). A New Multiwavelet-Based Approach to Image Fusion. Journal of Mathematical Imaging and Vision, 21: 177-192.

[7] Thamaraimanalan, T., RA, L., & RM, K. (2021). Multi Biometric Authentication using SVM and ANN Classifiers. Irish Interdisciplinary Journal of Science & Research, 5(1): 118-130.

[8] Das, S., Ghosh, S., Das, N. et al. (2018). Correction to: VLSI-Based Pipeline Architecture for Reversible Image Watermarking by Difference Expansion with High-Level Synthesis Approach. Circuits Syst Signal Process., 37, 5690.

[9] Thamaraimanalan T, Sampath P (2019). A low power fuzzy logic based variable resolution ADC for wireless ECG monitoring systems. Cogn Syst Res., 57: 236-245.

[10] T. Thamaraimanalan and P. Sampath (2019). Leakage Power Reduction in Deep Submicron VLSI Circuits using Delay based Power Gating. National Academy Science Letters, 43(3): 229-232.

[11] Kidav, J.U., Ajeesh, P.A., Vasudev, D., Deepak, V.S., Menon, A. (2013). A VLSI Architecture for Wavelet Based Image Compression. In: Meghanathan, N., Nagamalai, D., Chaki, N. (eds) Advances in Computing and Information Technology. Advances in Intelligent Systems and Computing, vol 178. Springer, Berlin, Heidelberg.

[12] Jonker, P.P. (1992). Pipelined low level image processing. In: Morphological Image Processing: Architecture and VLSI design. Springer, Boston, MA.

[13] Ranganathan, N., Nichani, S.J. & Mehrotra, R. (1991). A VLSI architecture for a half-edge-based corner detector. Machine Vis. Apps., 4: 165-181.