The Method of Hierarchical Multi-neighbor Predictors and Residual Orthogonal Transformations and Its Application to Image Compression(Practice, Wavelet Analysi, Special Issue on "Joint Symposium of JSIAM Activity Groups 2007")

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  • 多近傍情報による予測と残差直交変換の階層化およびその画像圧縮への応用(実用,ウェーブレット,<特集>平成19年研究部連合発表会)
  • 多近傍情報による予測と残差直交変換の階層化およびその画像圧縮への応用
  • タキンボウ ジョウホウ ニ ヨル ヨソク ト ザンサ チョッコウ ヘンカン ノ カイソウカ オヨビ ソノ ガゾウ アッシュク エノ オウヨウ

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Abstract

We propose new image compression algorithms by predicting each block using an improved gradient estimation at the block boundary followed by applying an orthogonal transformation to the prediction error. Compared to the previously proposed polyharmonic local cosine transform where the DC components of adjacent blocks were used for the gradient estimation, our new methods directly use multiple combinations of the neighboring pixel values to estimate the gradients at block boundary more accurately. Hence, we can improve the prediction of each block using such gradient information. Consequently, we can improve image reconstruction quality and reduce the blocking artifact and aliasing noise.

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