DeepAI
Log In Sign Up

Automatically eliminating seam lines with Poisson editing in complex relative radiometric normalization mosaicking scenarios

06/14/2021
by   Shiqi Liu, et al.
0

Relative radiometric normalization (RRN) mosaicking among multiple remote sensing images is crucial for the downstream tasks, including map-making, image recognition, semantic segmentation, and change detection. However, there are often seam lines on the mosaic boundary and radiometric contrast left, especially in complex scenarios, making the appearance of mosaic images unsightly and reducing the accuracy of the latter classification/recognition algorithms. This paper renders a novel automatical approach to eliminate seam lines in complex RRN mosaicking scenarios. It utilizes the histogram matching on the overlap area to alleviate radiometric contrast, Poisson editing to remove the seam lines, and merging procedure to determine the normalization transfer order. Our method can handle the mosaicking seam lines with arbitrary shapes and images with extreme topological relationships (with a small intersection area). These conditions make the main feathering or blending methods, e.g., linear weighted blending and Laplacian pyramid blending, unavailable. In the experiment, our approach visually surpasses the automatic methods without Poisson editing and the manual blurring and feathering method using GIMP software.

READ FULL TEXT

page 2

page 9

11/24/2021

Auto robust relative radiometric normalization via latent change noise modelling

Relative radiometric normalization(RRN) of different satellite images of...
10/16/2020

Semantic Editing On Segmentation Map Via Multi-Expansion Loss

Semantic editing on segmentation map has been proposed as an intermediat...
12/07/2020

Multi-temporal and multi-source remote sensing image classification by nonlinear relative normalization

Remote sensing image classification exploiting multiple sensors is a ver...
11/30/2021

SpaceEdit: Learning a Unified Editing Space for Open-Domain Image Editing

Recently, large pretrained models (e.g., BERT, StyleGAN, CLIP) have show...
04/14/2022

PLGAN: Generative Adversarial Networks for Power-Line Segmentation in Aerial Images

Accurate segmentation of power lines in various aerial images is very im...
05/31/2014

Combined Approach for Image Segmentation

Many image segmentation techniques have been developed over the past two...