Compressing video based on region of interest

Aziz, Hussein Muzahim; Fiedler, Markus; Grahn, Håkan; Lundberg, Lars

doi:10.1109/eurocon.2013.6625197

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2016

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“…Dumitras and Haskell drastically reduced the size while preserving textures by dividing the background according to the textures [12]. The method proposed by Azis et al used the technique of restoring areas other than the region of interest (ROI) using the time correlation between frames [13]. Zhang and Bull proposed a method for selecting an appropriate encoding method by dividing images into foreground and background areas and classifying the background into dynamic and static parts [14].…”

Section: Introductionmentioning

confidence: 99%

Efficient Coding for Video Including Text Using Image Generation

Yosuke

Miyazaki

Sugaya

et al. 2016

Journal of Information Processing

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Text in video compressed by lossy compression at a low bitrate will easily be deteriorated, resulting in blurred text and a lower readability. In this paper, we propose a novel image coding method to preserve the readability of text in the video at a very low bitrate. During the encoding process, we estimate the parameters for each character of the text. Then, an image without text is generated and compressed. During the decoding process, we reconstruct video sequences with text from images without text and character images generated by the estimated parameters. The experimental results show the effectiveness of the proposed method in terms of the readability at a very low bitrate.

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Section: Introductionmentioning

confidence: 99%