Challenges of 3D Surface Reconstruction in Capsule Endoscopy

There are currently many challenges specific to three-dimensional (3D) surface reconstruction using capsule endoscopy (CE) images. There are also challenges specific to viewing the content of CE reconstructed 3D surfaces for bowel disease diagnosis purposes. In this preliminary work, the author focuses on the latter and discusses the effects such challenges have on the content of reconstructed 3D surfaces from CE images. Discussions are divided into two parts. The first part focuses on the comparison of the content of 3D surfaces reconstructed using both preprocessed and non-preprocessed CE images. The second part focuses on the comparison of the content of 3D surfaces viewed at the same azimuth angles and different elevation angles of the line of sight. Experiments-based conclusion suggests 3D printing as a solution to the line of sight and 2D screen visual restrictions.Comment: 5 pages, 3 figure

Normalized Weighting Schemes for Image Interpolation Algorithms

This paper presents and evaluates four weighting schemes for image interpolation algorithms. The first scheme is based on the normalized area of the circle, whose diameter is equal to the minimum side of a tetragon. The second scheme is based on the normalized area of the circle, whose radius is equal to the hypotenuse. The third scheme is based on the normalized area of the triangle, whose base and height are equal to the hypotenuse and virtual pixel length, respectively. The fourth weighting scheme is based on the normalized area of the circle, whose radius is equal to the virtual pixel length-based hypotenuse. Experiments demonstrated debatable algorithm performances and the need for further research.Comment: 8 pages, 14 figure

Effects of rescaling bilinear interpolant on image interpolation quality

Rescaling bilinear (RB) interpolant's pixels is a novel image interpolation scheme. In the current study, we investigate the effects on the quality of interpolated images. RB determines the lower and upper bounds using the standard deviation of the four nearest pixels to find the new interval or range that will be used to rescale the bilinear interpolant's pixels. The products of the rescaled-pixels and corresponding distance-based-weights are added to estimate the new pixel value, to be assigned at the empty locations of the destination image. Effects of RB on image interpolation quality were investigated using standard full-reference and non-reference objective image quality metrics, particularly those focusing on interpolated images features and distortion similarities. Furthermore, variance and mean based metrics were also employed to further investigate the effects in terms of contrast and intensity increment or decrement. The Matlab based simulations demonstrated generally superior performances of RB compared to the traditional bilinear (TB) interpolation algorithm. The studied scheme's major drawback was a higher processing time and tendency to rely on the image type and/or specific interpolation scaling ratio to achieve superior performances. Potential applications of rescaling based bilinear interpolation may also include ultrasound scan conversion in cardiac ultrasound, endoscopic ultrasound, etc

Stochastic Rounding for Image Interpolation and Scan Conversion

The stochastic rounding (SR) function is proposed to evaluate and demonstrate the effects of stochastically rounding row and column subscripts in image interpolation and scan conversion. The proposed SR function is based on a pseudorandom number, enabling the pseudorandom rounding up or down any non-integer row and column subscripts. Also, the SR function exceptionally enables rounding up any possible cases of subscript inputs that are inferior to a pseudorandom number. The algorithm of interest is the nearest-neighbor interpolation (NNI) which is traditionally based on the deterministic rounding (DR) function. Experimental simulation results are provided to demonstrate the performance of NNI-SR and NNI-DR algorithms before and after applying smoothing and sharpening filters of interest. Additional results are also provided to demonstrate the performance of NNI-SR and NNI-DR interpolated scan conversion algorithms in cardiac ultrasound videos.Comment: 10 pages, 17 figures, 3 tables. International Journal of Advanced Computer Science and Applications, 202

Software Implementation of Optimized Bicubic Interpolated Scan Conversion in Echocardiography

This paper presents the image-quality-guided strategy for optimization of bicubic interpolation and interpolated scan conversion algorithms. This strategy uses feature selection through line chart data visualization technique and first index of the minimum absolute difference between computed scores and ideal scores to determine the image quality guided coefficient k that changes all sixteen BIC coefficients to new coefficients on which the OBIC interpolation algorithm is based. Perceptual evaluations of cropped sectored images from Matlab software implementation of interpolated scan conversion algorithms are presented. Also, IQA metrics-based evaluation is presented and demonstrates that the overall performance of the OBIC algorithm is 92.22% when compared with BIC alone, but becomes 57.22% with all other methods mentioned.Comment: 10 pages, 9 figures, 6 table