SAR Image Despeckling Convolutional Model with Integrated Frequency Filtration Technique
- Resource Type
- Conference
- Authors
- Saha, Anirban; Maji, Suman Kumar
- Source
- TENCON 2022 - 2022 IEEE Region 10 Conference (TENCON) Region 10 Conference (TENCON), TENCON 2022 - 2022 IEEE. :1-6 Nov, 2022
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Visualization
Filtration
Statistical analysis
Noise reduction
Speckle
Data models
Radar polarimetry
Synthetic aperture radar (SAR)
convolutional neural network (CNN)
feature preservation
speckle removal
SAR Despeckling
SAR denoising
- Language
- ISSN
- 2159-3450
The presence of unwanted multiplicative speckle noise within synthetic aperture radar (SAR) sensor data largely degrades its quality and challenges the processing of these data. Thus, in order to increase the performance of a SAR sensor data processing system, speckle removal techniques must be adopted. This paper demonstrates a novel framework that can be utilized to remove the presence of unwanted multiplicative speckle-noise within SAR images. The proposed framework is a convolutional neural network (CNN) based despeckling model with an integrated frequency-filtration based detail preservation module realized through skip connection. This configuration ensures maximal removal of speckle-noise from the raw input data with minimal compensation of sharp features present in the data. An extensive comparative analysis is carried out to study the performance of the proposed framework with other state-of-the-art despeckling models. This study has depicted the quantitative as well as visual performance superiority of the proposed model. Experimentation over real standard SAR data also demonstrates the superior performance of the proposed framework over other despeckling models present in the literature.