Effects of empty bins on image upscaling in capsule endoscopy

Abstract

This paper presents a preliminary study of the effect of empty bins on image upscaling in capsule endoscopy. The presented study was conducted based on results of existing contrast enhancement and interpolation methods. A low contrast enhancement method based on pixels consecutiveness and modified bilinear weighting scheme has been developed to distinguish between necessary empty bins and unnecessary empty bins in the effort to minimize the number of empty bins in the input image, before further processing. Linear interpolation methods have been used for upscaling input images with stretched histograms. Upscaling error differences and similarity indices between pairs of interpolation methods have been quantified using the mean squared error and feature similarity index techniques. Simulation results demonstrated more promising effects using the developed method than other contrast enhancement methods mentioned.

Advanced Image Enhancement Method for Distant Vessels and Structures in Capsule Endoscopy

“…In Tables 1 and 2 , M1 represents the method proposed in [ 3 ], M2 represents the method proposed in [ 4 ], and PM represents the method proposed in this paper.…”

“…Unlike in the M1 and M2 cases, the PM produced brighter images, but not too bright, and preserved the hue. It is important to note that Histogram Equalization (HE), Adaptive HE (AHE), and Contrast-Limited AHE (CLAHE) terribly change the hue of reference images, in RGB color space, as demonstrated in [ 3 , 9 ]. Therefore, the capsule endoscopic images enhanced by such methods have not been included in this part.…”

“…To clinically benefit from images obtained thanks to the capsule endoscope (CE), it is important to develop an advanced method that would deal carefully with the poor contrast problem caused generally by poor visibility conditions of the GI tract [ 17 ]. In this regard, a novel method using exclusively the bilinear interpolation algorithm has been proposed in [ 4 ] to deal with (1) the creation of artefacts leading to unnatural colors of the Histogram Equalization (HE) based methods without the need for converting Red-Blue-Green (RGB) to another color space [ 9 , 10 ] and (2) the disadvantages of the generalized overexposure problem of the method proposed previously in [ 3 ]. Although experimental demonstrations showed that the half-unit weighted-bilinear algorithm (HWB), proposed in [ 4 ], made considerable improvements over the method proposed in [ 3 ], (improvements that can also be seen/noticed in this paper Figures 5(a) – 11(a) ), a gastroenterologist (ØH) could only rate highly 70% of enhanced images presented in experimental demonstrations of [ 4 ].…”

Effects of rescaling bilinear interpolant on image interpolation quality

“…It is based on performing interpolation in two directions. As can be seen, in Figure 1's example, the bilinear interpolation algorithm uses four nearest pixels or samples in Equation 1 to estimate or approximate the missing pixel value at ( , ) P x y , [11], [12].…”

Aliasing artefact index for image interpolation quality assessment

“…In the current literature, there exist many interpolation algorithms developed for different purposes [4], [5], [13], [16], [18], but here, a great interest has been put on the NN algorithm. Equation 1 is the basic linear scaling equation on which the NN interpolation algorithm is based.…”