Advancements in remote sensing over the past two decades have enabled the production of high-resolution multispectral imagery, necessitating improved analytical methods. Object-Based Image Analysis (OBIA) has become a principal approach with image segmentation being a critical initial step. This study examines various image segmentation methods, particularly focusing on semantic segmentation for cloud images. Accurate cloud detection in satellite imagery is vital for numerous applications, leading to the development of Cloud-Net, an end-to-end cloud detection algorithm utilizing a Fully Convolutional Network (FCN) based on a U-Net architecture. This research implements atrous convolution on Cloud-Net in both contracting and expanding blocks, reinstating vanilla skip connections to reduce complexity. Experimental results using Landsat 8 imagery demonstrate that while the proposed Atrous Cloud-Net improves precision and specific metrics evaluation for grayscale images, the original Cloud-Net performs better for RGB images. The findings highlight the trade-offs between different segmentation methods and the importance of multi-channel imagery for higher accuracy in cloud detection tasks. Future work will focus on further refining segmentation models and exploring additional channels to enhance performance.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Implementation of Atrous Convolution for Cloud Segmentation in Grayscale & RGB Images from Landsat 8


    Contributors:


    Publication date :

    2024-11-08


    Size :

    647157 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Semantic Segmentation with Inverted Residuals and Atrous Convolution

    Kong, Huifang / Fan, Lei / Zhang, Xiaoxue | SAE Technical Papers | 2018


    Semantic Segmentation with Inverted Residuals and Atrous Convolution

    Kong, Huifang / Fan, Lei / Zhang, Xiaoxue | British Library Conference Proceedings | 2018


    AANet: Motorcycle ReID Using Multi-Atrous Convolution and Self-Attention Mechanisms

    Nguyen-Mau, Trong-Hieu / Phu-Thi, Kim-Trang / Le-Dinh, Anh-Duy et al. | IEEE | 2023


    Knowledge-based segmentation of Landsat images

    Ton, J. / Sticklen, J. / Jain, A.K. | Tema Archive | 1991


    Extraction of Shape Skeletons from Grayscale Images

    Sibel Goktepe Tari, Z. / Shah, J. / Pien, H. | British Library Online Contents | 1997