Segmentation of high resolution satellite imagery based on mean shift algorithm and morphological operations

Date

2009-11-04

Author

Aytekin, Örsan
Ulusoy, İlkay
Halıcı, Uğur

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

47
views

0
downloads

Data-driven unsupervised segmentation of high resolution remotely sensed images is a primary step in understanding remotely sensed images. A new fully automatic method to delineate the segments corresponding to objects in high resolution remotely sensed images is introduced. There are extensive methods proposed in the literature which are mainly concentrated on pixel level information. The proposed method combines the structural information extracted by morphological processing with feature space analysis based on mean shift algorithm. The spectral and spatial bandwidth parameters of mean shift are adaptively determined by exploiting differential morphological profile (DMP), Spectral bandwidth is determined in relation to the first maximum value of DMP at each pixel and spatial bandwidth is determined by the corresponding index in DMP. in this method there is also no need to specify initially the maximum size of the structuring element for the morphological processes. By the use of mean shift filtering, the feature space points are grouped together which are close to each other both in the range of spatial and spectral bandwidths. The proposed method is applied on panchromatic high resolution QuickBird satellite images taken from urban areas. The results we obtained appear to be effective in terms of segmentation and combining the spectral and spatial information to extract more precise and more meaningful objects compared to fixed bandwidth mean shift segmentation. © 2009 SPIE.

URI

https://hdl.handle.net/11511/57556

DOI

https://doi.org/10.1117/12.830456

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Alignment of uncalibrated images for multi-view classification Arık, Sercan Ömer; Vural, Elif; Frossard, Pascal (2011-12-29) Efficient solutions for the classification of multi-view images can be built on graph-based algorithms when little information is known about the scene or cameras. Such methods typically require a pairwise similarity measure between images, where a common choice is the Euclidean distance. However, the accuracy of the Euclidean distance as a similarity measure is restricted to cases where images are captured from nearby viewpoints. In settings with large transformations and viewpoint changes, alignment of im...
Contrast Enhancement of Microscopy Images Using Image Phase Information Çakır, Serhat; Atalay, Rengül; ÇETİN, AHMET ENİS (2018-01-01) Contrast enhancement is an important preprocessing step for the analysis of microscopy images. The main aim of contrast enhancement techniques is to increase the visibility of the cell structures and organelles by modifying the spatial characteristics of the image. In this paper, phase information-based contrast enhancement framework is proposed to overcome the limitations of existing image enhancement techniques. Inspired by the groundbreaking design of the phase contrast microscopy (PCM), the proposed ima...
Automatic segmentation of VHR images using type information of local structures acquired by mathematical morphology AYTEKİN, orsan; Ulusoy, İlkay (Elsevier BV, 2011-10-01) The morphological profile (MP) and differential morphological profile (DMP) have been used extensively to acquire spatial information to be used in the segmentation of very high resolution (VHR) remotely sensed images. In most of the previous approaches, the maxima of the MP and DMP were investigated to estimate the best representative scale in the spatial domain for the pixel under consideration. Then, the object type (i.e. dark, bright or flat) was estimated based on the location of the maximum. Finally, ...
Visual similarity for hdr images with applications to tone mapping Aydınlılar, Merve; Akyüz, Ahmet Oğuz; Tarı, Zehra Sibel; Department of Computer Engineering (2021-2-15) Assessing visual similarity between images is important for many computer vision applications. So far, investigations on visual similarity have been confined to low dynamic range images. However, recently, there is a growing interest to high dynamic range (HDR) imaging. In this thesis, the aim is to shed light on visual image similarity for HDR images by following an experimental approach. To this end, a user experiment is conducted through a novel web-based interface, in which the participants assess the p...
Anlık Spektral Görüntüleme için Tasarım Eniyileme Ayazgök, Suleyman; Öktem, Sevinç Figen (2019-08-22) Snapshot spectral imaging enables to reconstructspectral images from a multiplexed single-shot measurement.Since an inversion is required to form the spectral images com-putationally, quantitative characterization of their performanceis essential to optimize the design. In this paper, we analyze theoptimal design of a snapshot spectral imaging technique. Thissnapshot multi-spectral imaging technique uses a diffractive lenscalled generalized photon sieve, and vari...

Citation Formats

Ö. Aytekin, İ. Ulusoy, and U. Halıcı, “Segmentation of high resolution satellite imagery based on mean shift algorithm and morphological operations,” 2009, vol. 7477, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/57556.