Endoscopy image restoration: A study of the kernel estimation from specular highlights.

Endoscopy images show part of the gastrointestinal tract or other parts of the human body. Due to the complex environment in which this tract is located in the human body and the limitations of the image acquisition equipment, endoscopy images may present blur and specular highlights that are common types of degradation. In this paper, we present a blind deblurring approach for endoscopy images that estimate the blur kernel from the fusion of the specular highlights. The proposed method can be divided into two phases. First, the specular highlights are precisely extracted from the original image using a sparse and low-rank image decomposition approach. Then, these highlights are automatically clustered and fused according to the spatial and intensity features. In this way, potential kernels are generated and used for the deblurring process. The experimental results show that the proposed method presents an improved and comparable performance when considered other state-of-the-art methods that use highlights segmentation and image deblurring.