Abstract
This paper proposes a two-stage high-order intrablock prediction method for light field image coding. This method exploits the spatial redundancy in lenslet light field images by predicting each image block, through a geometric transformation applied to a region of the causal encoded area. Light field images comprise an array of microimages that are related by complex geometric transformations that cannot be efficiently compensated by state-of-the-art image coding techniques, which are usually based on low-order translational prediction models. The two-stage nature of the proposed method allows us to choose the order of the prediction model most suitable for each block, ranging from pure translations to projective or bilinear transformations, optimized according to an appropriate rate-distortion criterion. The proposed higher order intrablock prediction approach was integrated into a high efficiency video coding (HEVC) codec and evaluated for both unfocused and focused light field camera models, using different resolutions and microlens arrays. Experimental results show consistent bitrate savings, which can go up to 12.62%, when compared to a lower order intrablock prediction solution and 49.82% when compared to HEVC still picture coding.
Highlights
Light Field (LF) imaging technology available in lenslet LF cameras allows to jointly capture radiance data and angular information from the light rays hitting the camera’s sensor, by means of multiplexing the LF data in a 2D conventional sensor
This paper proposes a two-stage high order intra block prediction method for light field image coding
Light field images comprise an array of micro-images that are related by complex geometric transformations that cannot be efficiently compensated by state-of-the-art image coding techniques, which are usually based on low order translational prediction models
Summary
Light Field (LF) imaging technology available in lenslet LF cameras allows to jointly capture radiance data and angular information from the light rays hitting the camera’s sensor, by means of multiplexing the LF data in a 2D conventional sensor. Like translation, rotation, scale, shear and perspective changes have been used to improve the coding efficiency, by exploiting spatial [7], temporal [8]– [13] and inter-view [14]–[17] redundancy In most proposals, these models have been applied image-wise (instead of blockwise), due to two main reasons: (i) high computational complexity in block-wise model parameter estimation, and (ii) significant additional bit rate required for parameter transmission. The remainder of this paper is organized as follows: Section II presents a review of several relevant state-of-the-art solutions, regarding LF image coding; Section III describes the geometric transformations used in the proposed prediction method; Section IV presents the proposed HOP model; Section V presents the test conditions and experimental results; and, Section VI concludes the paper
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