Kyushu University Academic Staff Educational and Research Activities Database
List of Presentations
Naoki Ono Last modified date:2023.11.27

Associate Professor / Image Information Engineering / Department of Media Design / Faculty of Design


Presentations
1. Halftoning by Inverse Box Filter.
2. Super-Resolution Reconstruction of 360-Degree Images Using Overset Grid Method.
3. A Method of Video Super-Resolution Processing Using Deep Learning.
4. Super-resolution Processing Embedded with Attribute Information.
5. Super-resolution Processing Embedded with Attribute Information.
6. Super-resolution Processing of Face Images Considering Attribute Information.
7. Image Enhancement with Locally Projected Brightness.
8. Improvement of Excessive Edge Enhancement by Using Bilateral Filter.
9. Image Enhancement with Suppressing Edge Distortion by Using Nonlinear Filter.
10. Image Enhancement with Suppressing Edge Distortion by Using Bilateral Filter.
11. Yu Gu, Naoki Ono, kiichi urahama, Ink-painting Animation by Geometry Buffer Based Real-time 3D Rendering, The 4th IIAE International Conference on Intelligent Systems and Image Processing (ICISIP), 2016.09, We propose a technique using geometry buffers for real-time rendering of 3D ink-wash paintings. According to the characteristics of hand-drawn ink-wash paintings, contour lines and coloring area in the ink paintings are stylized by rendering 3D models to 2D texture images. Entire rendering computation is implemented with a GPU for enabling its real-time processing on commercially available computers..
12. Naoki Ono, kiichi urahama, Comparing Interpolations in Frequency Domain and Improvement of Interpolated Images by Using Cube of Pixel Difference, The 4th IIAE International Conference on Intelligent Systems and Image Processing (ICISIP), 2016.09, We propose a method for improving image resolution. The method consists of an interpolation and a sharpening process. We research about some interpolations for producing high resolution images and show the properties of the interpolations in the frequency domain. Based on the research, we selected Lanczos function for the interpolation and applied the sharpening method which uses weighted sum of cubic operations of the pixel differences to the interpolated image. Experimental results also show that the sharpening with Lanczos interpolation gives clear high resolution images..
13. Naoki Ono, kiichi urahama, Sharpening Interpolated Image by Using Cube of Pixel Difference, The 3rd IIAE International Conference on Intelligent Systems and Image Processing (ICISIP), 2015.09, In order to improve image resolution, any interpolation has to be applied. However, in general, interpolation generates smooth connections between adjacent sampling points and yields blurred edges in the interpolated image. To suppress such a blur in edges, it is desired to include any sharpening effect in the interpolating process. In this paper, we propose a sharpening method using cubic operations of the differences of pixel values. Experimental results show that this method produces sharp high resolution image which is more similar to a target image than that by any other method..
14. Sharpening Interpolated Image by Cubic Unsharp Operation of Pixel Difference.
15. Image Sharpening by Cubic Unsharp Operation of Pixel Diffrence.
16. Evaluations of Image Quality Improvement without Reference.
17. Estimation of parameters in image processing based on an image improvement evaluation function.
18. A Unified Formulation of Weighted Averaging Filter and Unsharp Pasking and its Application to Miniature Photograpy.
19. Zihan Yu, Kohei Inoue, Kenji Hara, Naoki Ono, kiichi urahama, Bilateral Minimum Filter for Dehazing Images, 11th International Conference on Quality Control by Artificial Vision , 2013.06.
20. Ono Naoki, urahama kiichi, Image Improvement by Using Noise Suppressing Unsharp Masking and Evaluation without Reference, International Workshop on Advanced Image Technology 2013, 2013.01, The technique of Unsharp Masking(UM) are often applied for improving the image quality. However, for images with added noises, UM causes the amplification of noise, which often makes the method not usable in practice. In this paper, we propose a new UM method with suppressing the noise amplification. The proposed method reduces noise amplification and permits to obtain perceptually pleasant results. Furthermore we show a method for evaluating the improvement after unsharp masking processes. The new UM method has parameters to be set in advance. The evaluation method can be used to set the parameters for obtaining well improved results. .
21. A method for evaluating the improvement of image quality after any image processing.
22. A Digital Image Enlargement Based on Curvature with Edge Information.
23. Image Quality Improvement by Using Noise Suppressing Unsharp Masking.
24. A Digital Image Enlargement Based on Curvature with Efficient Calculation.
25. Unsharp Masking Procedure Suppressing Enhancement of Noise.
26. A Digital Image Enlargement Based on Curvature with Edge Preserved.
27. An Iterative Interpolation for Digital Image Based on Curvature .
28. An Interpolation Based on Curvature for Digital Image Enlargement.
29. Halftoning by Iterative Error Diffusion Preserving Piecewise Smoothness.
30. Edge-Preserving Error-Diffusion with Cross Bilateral Filter.
31. Rotation Angle Estimation of Scaled Object by Using Sets of Perpendicular Bisectors.
32. Rotation Angle Estimation by Using Perpendicular Bisectors on Contours.
33. Rotation Angle Estimation by Using Sets of Perpendicular Bisectors on Contours.
34. Development of a Measurement System of Head Related Impulse Response for All Azimuthal Directions with Discrete Elevations and Resulting Measurement Accuracy.
35. Rotation Angle Estimation of an Object Described with Un-continuous Outline by Using Pseudo Gradient.
36. Motion Detection by Using Iterative Extraction of Clusters.
37. Motion Detection Using Fuzzy Hough Transform.
38. Iterative Extraction of Clusters without Deletion of Detected Cluster Data.
39. A Correction of Restored Image Obtained by a Regularized Inverse Filter.
40. On calculation of curvature of sampled curves.
41. Restoration of rotationally blurred images
A method is proposed to restore rotationally blurred images, where an efficient coordinate transformation and an iterative restoring method are combined, taking into account noise. The transformation is more advantageous for the purpose than the usual one. In addition, since the restoration is performed iteratively, it requires less memory space and so it can be realized even on a personal computer..