Segmentation method based on multiobjective optimization for very high spatial resolution satellite images

Joumani, Saleh El; Mechkouri, Salah Eddine; Zennouhi, Rachid; Kadmiri, Omar El; Masmoudi, Lhoussaine

doi:10.1186/s13640-016-0161-2

Cited by 7 publications

(9 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 3 presents the segmented results for synthetic images. In addition, the table 2 illustrate the results obtained by our method and their challenging with the method [5]; it authenticates that the good results obtained by our developed method.…”

Section: Resultssupporting

confidence: 77%

“…To study the influence of small regions, the first image we preferred contained a texture. We observed that the values of the inter-region, intra-inter-region and MSE criteria of our proposed method are lower than those provided by the method [5], and the intra-region criterion values are superior. The same findings obtained when processing other synthetic images having different morphological properties.…”

Section: Resultsmentioning

confidence: 62%

“…The empirical results of our method show that the Tsallis and Rényi entropies offer competitive segmentation performances compared to the results of the formerly method [5]. Therefore, they depict the validity of our method; we will test and apply them to synthetic images and evaluate our Worldview image segmentation algorithm of the desert environment.…”

Section: Introductionmentioning

confidence: 83%

“…One of the most intuitive criteria for quantifying the eminence of a segmentation result is the intra-region uniformity. Allowing to Weszka et al [13], Levine and Nazif [16] and El Joumani et al [5] the criterion of intra-region uniformity is as follows:…”

Section: Levine and Nazif Criterion A Intra-region Uniformitymentioning

confidence: 99%

“…First, we explore the centers of gravity of each gray-scale image region and the corresponding thresholds in their histograms according to Mechkouri et al [1,2], Sarala et al [3] and Zennouhi et al [4]. In order to reveal the opportunity of our proposed method, we compared it with that developed in 2017 by EL Joumani et al [5]. Secondly, we will evaluate our algorithm by the image segmentation of the desert environment.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Multi-Objective Optimization for Worldview Image Segmentation Funded on the Entropies of Tsallis and Rényi

Mechkouri¹

2019

IJATCSE

Self Cite

View full text Add to dashboard Cite

The article describes a new method of threshold satellite image, based on the optimization multi-objective for segmentation of Worldview images and funded on the Tsallis and the Rényi entropies, allowing the evolution of the satellite image classification. Owing to the goal of achieving a large classifying all unclassified pixels by the previous method in 2017 in our research laboratory. An improved analysis and a multi-objective optimized thresholding method was proposed. Firstly, we are calculate the optimal thresholds with respect to the criteria retained such as the Tsallis criterion and the Rényi criterion. Lastly, we are challenging the performance of our method to that developed previously in 2017. The new method effectiveness evaluation confirmed by the calculation of the evaluation criterion related on both the Levine and Nazif criterion and the Mean Squared Error criterion. The results obtained by our approach were very satisfactory. It was been shown that the method overcomes the difficulties of the method previously developed in 2017 and obtained results that are more precise. In particular, for synthetic images, the segmentation accuracy increases by 81.16% and for the satellite images, the segmentation also improves enormously, and the accuracy of the overall classification of Worldview images increases by 97.21%. Therefore, the new method based on multi-objective optimization contribute significantly to performance.

show abstract

Section: Resultssupporting

confidence: 77%

Section: Resultsmentioning

confidence: 62%

Section: Introductionmentioning

confidence: 83%

Section: Levine and Nazif Criterion A Intra-region Uniformitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Multi-Objective Optimization for Worldview Image Segmentation Funded on the Entropies of Tsallis and Rényi

Mechkouri¹

2019

IJATCSE

Self Cite

View full text Add to dashboard Cite

show abstract

Color image segmentation using saturated RGB colors and decoupling the intensity from the hue

García-Lamont

Cervantes

López-Chau

et al. 2019

Multimed Tools Appl

View full text Add to dashboard Cite

Although the RGB space is accepted to represent colors, it is not adequate for color processing. In related works the colors are usually mapped to other color spaces more suitable for color processing, but it may imply an important computational load because of the non-linear operations involved to map the colors between spaces; nevertheless, it is common to find in the state-of-the-art works using the RGB space. In this paper we introduce an approach for color image segmentation, using the RGB space to represent and process colors; where the chromaticity and the intensity are processed separately, mimicking the human perception of color, reducing the underlying sensitiveness to intensity of the RGB space. We show the hue of colors can be processed by training a selforganizing map with chromaticity samples of the most saturated colors, where the training set is small but very representative; once the neural network is trained it can be employed to process any given image without training it again. We create an intensity channel by extracting the magnitudes of the color vectors; by using the Otsu method, we compute the threshold values to divide the intensity range in three classes. We perform experiments with the Berkeley segmentation database; in order to show the benefits of our proposal, we perform experiments with a neural network trained with different colors by subsampling the RGB space, where the chromaticity and the intensity are processed jointly. We evaluate and compare quantitatively the segmented images obtained with both approaches. We claim to obtain competitive results with respect to related works.

show abstract

Multi-objective optimization for worldview image segmentation funded on the entropies of Tsallis and Rényi

Mechkouri¹,

Joumani²,

Zennouhi³

et al. 2020

Multimed Tools Appl

View full text Add to dashboard Cite

Segmentation method based on multiobjective optimization for very high spatial resolution satellite images

Cited by 7 publications

References 18 publications

Multi-Objective Optimization for Worldview Image Segmentation Funded on the Entropies of Tsallis and Rényi

Multi-Objective Optimization for Worldview Image Segmentation Funded on the Entropies of Tsallis and Rényi

Color image segmentation using saturated RGB colors and decoupling the intensity from the hue

Multi-objective optimization for worldview image segmentation funded on the entropies of Tsallis and Rényi

Contact Info

Product

Resources

About