Gradient Estimation in Uncertain Data
نویسندگان
چکیده
Detecting edges in images which are distorted by unreliable or missing data samples can be done using normalized (differential) convolution. This work presents a comparison between gradient estimation using normalized convolution and gradient estimation using normalized differential convolution with regard to speed, accuracy, and noisesensitivity.
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