Robust, object-based high-resolution image reconstruction from low-resolution video

Date

1997-10-01

Author

Eren, Pekin Erhan
Sezan, MI
Tekalp, AM

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

145
views

0
downloads

We propose a robust, object-based approach to high-resolution image reconstruction from video using the projections onto convex sets (POCS) framework. The proposed method employs a validity map and/or a segmentation map. The validity map disables projections based on observations with inaccurate motion information for robust reconstruction in the presence of motion estimation errors; while the segmentation map enables object-based processing where more accurate motion models can be utilized to improve the quality of the reconstructed image. Procedures for the computation of the validity map and segmentation map are presented. Experimental results demonstrate the improvement in image quality that can be achieved by the proposed methods.

Subject Keywords

high-resolution reconstruction, object-based reconstruction, POCS, segmentation, tracking, SEQUENCES, MOTION

URI

https://hdl.handle.net/11511/100397

Journal

IEEE TRANSACTIONS ON IMAGE PROCESSING

DOI

https://doi.org/10.1109/83.624970

Collections

Graduate School of Informatics, Article

Suggestions

OpenMETU
Core

Piecewise-planar 3D reconstruction in rate-distortion sense Imre, Evren; Gueduekbay, Ugur; Alatan, Abdullah Aydın (2007-05-09) In this paper, a novel rate-distortion optimization inspired 3D piecewise-planar reconstruction algorithm is proposed. The algorithm refines a coarse 3D triangular mesh, by inserting vertices in a way to minimize the intensity difference between an image and its prediction. The preliminary experiments on synthetic and real data indicate the validity of the proposed approach.
QUALITY EVALUATION OF STEREOSCOPIC VIDEOS USING DEPTH MAP SEGMENTATION Sarikan, Selim S.; Olgun, Ramazan F.; Akar, Gözde (2011-09-09) This paper presents a new quality evaluation model for stereoscopic videos using depth map segmentation. This study includes both objective and subjective evaluation. The goal of this study is to understand the effect of different depth levels on the overall 3D quality. Test sequences with different coding schemes are used. The results show that overall quality has a strong correlation with the quality of the background, where disparity is smaller relative to the foreground. The results also showed that con...
TEMPORALLY CONSISTENT LAYER DEPTH ORDERING VIA PIXEL VOTING FOR PSEUDO 3D REPRESENTATION Turetken, Engin; Alatan, Abdullah Aydın (2009-05-06) A new region-based depth ordering algorithm is proposed based on the segmented motion layers with affine motion models. Starting from an initial set of layers that are independently extracted for each frame of an input sequence, relative depth order of every layer is determined following a bottom-to-top approach from local pair-wise relations to a global ordering. Layer sets of consecutive time instants are warped in two opposite directions in time to capture pair-wise occlusion relations of neighboring lay...
TEXTURE PRESERVING MULTI FRAME SUPER RESOLUTION WITH SPATIALLY VARYING IMAGE PRIOR Turgay, Emre; Akar, Gözde (2012-10-03) This paper proposes a new maximum a posteriori (MAP) based super-resolution (SR) image reconstruction method targeting edges and textures in images. Unlike conventional MAP based SR image reconstruction methods a spatially varying image prior is employed which is updated according to the frequency content of the reconstructed image at each iteration at different locations. Two alternative methods based on discrete cosine transforms (DCT) and Gabor filters are proposed for determining the image prior. The pr...
Keyframe based bi directional 2 D mesh representation for video object tracking and manipulation Eren, Pekin Erhan (1999-10-28) We propose a new bi-directional 2-D mesh representation of video objects, which utilizes multiple keyframes with forward and backward tracking. Experimental results on use of this representation for video object tracking in the presence of self occlusion are presented.

Citation Formats

P. E. Eren, M. Sezan, and A. Tekalp, “Robust, object-based high-resolution image reconstruction from low-resolution video,” IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 6, no. 10, pp. 1446–1451, 1997, Accessed: 00, 2022. [Online]. Available: https://hdl.handle.net/11511/100397.