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Pansharpening of Multispectral Images Through the Inverse Problem Model with Non-convex Sparse Regularization

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Intelligent Control, Robotics, and Industrial Automation (RCAAI 2022)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1066))

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Abstract

Pansharpening is considered as an imperative process for various remote sensing applications viz. crop monitoring, hazard monitoring, object detection and classification etc. The Pansharpening technique combines panchromatic and multispectral pictures to create a high resolution multispectral image. In this paper, the pansharpening approach and a variational optimization model are discussed. As an ill-posed inverse issue, a cost function is proposed, with three prior components, two of which are data-fidelity terms generated from the relationship between the source and output images. The third term is integrated to regularize the formulated inverse model. The eminent solver, alternating direction method of multipliers in conjunction with iterative minimization mechanism is employed to obtain the comprehensive minimum of the proposed convex cost function. The minimized solution is the required pansharpened image. The effectiveness of the suggested strategy is assessed using three different datasets and four recognized indicators. The results, both objective and subjective, show the effectiveness of the variational optimization pansharpening (VOPS) model. The merged image has greatly improved spectral and spatial properties.

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Author information

Authors and Affiliations

  1. Department of ECE, Dhanekula Institute of Engineering and Technology, Vijayawada, 521139, India

    Rajesh Gogineni, Y. Ramakrishna & P. Veeraswamy

  2. School of electronics engineering, VITAP University, Amaravati, India

    Jannu Chaitanya

Authors
  1. Rajesh Gogineni
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  2. Y. Ramakrishna
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  3. P. Veeraswamy
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  4. Jannu Chaitanya
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Corresponding author

Correspondence to Rajesh Gogineni .

Editor information

Editors and Affiliations

  1. School of Engg., Computing and Math.,, University of Plymouth, Plymouth, UK

    Sanjay Sharma

  2. School of Electrical Sciences, Indian Institute of Technology Goa, Ponda, Goa, India

    Bidyadhar Subudhi

  3. Department of Mechatronics, Manipal Institute of Technology, Manipal, Karnataka, India

    Umesh Kumar Sahu

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Gogineni, R., Ramakrishna, Y., Veeraswamy, P., Chaitanya, J. (2023). Pansharpening of Multispectral Images Through the Inverse Problem Model with Non-convex Sparse Regularization. In: Sharma, S., Subudhi, B., Sahu, U.K. (eds) Intelligent Control, Robotics, and Industrial Automation. RCAAI 2022. Lecture Notes in Electrical Engineering, vol 1066. Springer, Singapore. https://doi.org/10.1007/978-981-99-4634-1_40

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