DESPECKLING ALGORITHM FOR REMOTE SENSING SYNTHETIC APERTURE RADAR IMAGES USING MULTI-SCALE CURVELET TRANSFORM

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kooshesh Monireh; AKBARIZADEH GHOLAMREZA

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL SYMPOSIUM ON ARTIFICIAL INTELLIGENCE AND SIGNAL PROCESSING (AISP)
Year:2015 | Issue:1

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Title

DESPECKLING ALGORITHM FOR REMOTE SENSING SYNTHETIC APERTURE RADAR IMAGES USING MULTI-SCALE CURVELET TRANSFORM

Author(s)

kooshesh Monireh | AKBARIZADEH GHOLAMREZA | Issue Writer Certificate

Keywords

CURVELET TRANSFORM

WAVELET

FDCT

SYNTHETIC APERTURE RADAR IMAGES

DESPECKLING

UNSUPERVISED

TEXTURE

FEATURE

SEGMENTATION

Abstract

THE GOAL OF THE PRESENT RESEARCH IS TO DESPECKLE SAR IMAGES, WHICH IS CRITICAL FOR SEGMENTATION AND TARGET RECOGNITION IN SATELLITE SAR IMAGES. WHEN A DESPECKLING ALGORITHM IS APPLIED TO A SAR IMAGE, IMPORTANT INFORMATION SUCH AS THE EDGES, CORNERS, TEXTURES, AND OBJECT PARTS WILL DEGRADE. CURVELET TRANSFORM IS A RECENTLY PROPOSED FORM OF MULTI-SCALE ANALYSIS THAT ACHIEVES BETTER PERFORMANCE OF WAVELET AND GABOR TRANSFORMS IN EDGE AND CURVE DETECTION. THIS IS A GEOMETRIC TRANSFORM THAT IS USEFUL FOR SAR IMAGE PROCESSING. FOR UNSUPERVISED TEXTURE IMAGES, SEGMENTATION IS DIFFERENT AND DISTINCT FROM THE TEXTURES, SO THE TEXTURES AT THE BOUNDARY NOISES WILL DISAPPEAR. CURVELET TRANSFORM HAS PRODUCED GOOD RESULTS IN THE DETECTION OF CURVED EDGES WITH HIGHER ACCURACY IN FINDING THE ORIENTATION THAN WAVELET TRANSFORMS. THE PRESENT STUDY USES FAST DISCRETE CURVELET TRANSFORM (FDCT) BASED ON WRESTING AND USES UNSUPERVISED ADAPTIVE THRESHOLD LEARNING TO DEVELOP A NEW DESPECKLING ALGORITHM FOR SAR IMAGES. IN THE PROPOSED ALGORITHM, EACH SEGMENT OF THE SAR IMAGE CAN BE LEARNED FOR SELECTION OF ITS ADAPTIVE THRESHOLD. SIMULATION RESULTS DEMONSTRATE THAT THE PROPOSED ALGORITHM PERFORMS BETTER THAN SIMILAR METHODS. ...

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APA: Copy

kooshesh, Monireh, & AKBARIZADEH, GHOLAMREZA. (2015). DESPECKLING ALGORITHM FOR REMOTE SENSING SYNTHETIC APERTURE RADAR IMAGES USING MULTI-SCALE CURVELET TRANSFORM. INTERNATIONAL SYMPOSIUM ON ARTIFICIAL INTELLIGENCE AND SIGNAL PROCESSING (AISP). SID. https://sid.ir/paper/927512/en

Vancouver: Copy

kooshesh Monireh, AKBARIZADEH GHOLAMREZA. DESPECKLING ALGORITHM FOR REMOTE SENSING SYNTHETIC APERTURE RADAR IMAGES USING MULTI-SCALE CURVELET TRANSFORM. 2015. Available from: https://sid.ir/paper/927512/en

IEEE: Copy

Monireh kooshesh, and GHOLAMREZA AKBARIZADEH, “DESPECKLING ALGORITHM FOR REMOTE SENSING SYNTHETIC APERTURE RADAR IMAGES USING MULTI-SCALE CURVELET TRANSFORM,” presented at the INTERNATIONAL SYMPOSIUM ON ARTIFICIAL INTELLIGENCE AND SIGNAL PROCESSING (AISP). 2015, [Online]. Available: https://sid.ir/paper/927512/en

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