Unsupervised Estimation of the Equivalent Number of Looks Based on Edge Strength Map in SAR Images

Combining with Edge Strength Map (ESM), an unsupervised estimation of the Equivalent Number of Looks (ENL) in SAR images is proposed. First, ESM is produced by ratio operation of anisotropic Gaussian kernel parallel windows. On the basis of simple image partition processing, the local ESM thresholds for image blocks are obtained by an effective unsupervised estimation method, and SAR image is divided into homogeneous regions and edge regions by shrinkage ESM. Under twice restrictions based on ESM, each local ENL of all pixels in homogeneous regions is estimated by irregular window with large scale. Then global ENL of SAR image is acquired by histogram statistical method for all local ENL values. Experimental results show that the proposed method can get over serious adverse effects to estimation value by the selection of local statistics methods in estimation methods based on spatial statics, and can avoid the need for apriority information on speckle and being an ineffective estimation for despeckling SAR images in estimation methods based on statistical model.