One Pass Quality Control and Low Complexity RDO in A Quadtree Based Scalable Image Coder

International audienceThis paper presents a joint quality control (QC) and rate distortion optimization (RDO) algorithm applied to a still image codec called Locally Adaptive Resolution (LAR). LAR supports scalability in resolution for both lossy and lossless coding and has low complexity. This algorithm is based on the study of the relationship between compression efficiency and relative parameters. The RDO model is proposed firstly to find suitable parameters. Relying on this optimization, relationships between the distortion of reconstructed image and quantization parameter can be described with a new linear model. This model is used for parametric configuration to control compression distortion. Experimental results show that this algorithm provides an effective solution for an efficient one pass codec with automatic parameters selection and accurate QC. This algorithm could be extended to codecs with similar functions, such as High Efficiency Video Coding (HEVC)

Low Complexity RDO Model for Locally Subjective Quality Enhancement in LAR Coder

International audienceThis paper introduces a rate distortion optimization (RDO) scheme with subjective quality enhancement applied to a still image codec called Locally Adaptive Resolution (LAR). This scheme depends on the study of the relation between compression efficiency and relative parameters, and has a low complexity. Linear models are proposed first to find suitable parameters for RDO. Next, these models are combined with an image segmentation method to improve the local image quality. This scheme not only keeps an effective control in balance between bitrate and distortion, but also improves the spatial structure of images. Experiments are done both in objective and subjective ways. Results show that after this optimization, LAR has an efficient improvement of subjective image quality of decoded images. This improvement is significantly visible and compared with other compression methods using objective and subjective quality metrics

Low Complexity RDO Model for Locally Subjective Quality Enhancement in LAR Coder

International audienceThis paper introduces a rate distortion optimization (RDO) scheme with subjective quality enhancement applied to a still image codec called Locally Adaptive Resolution (LAR). This scheme depends on the study of the relation between compression efficiency and relative parameters, and has a low complexity. Linear models are proposed first to find suitable parameters for RDO. Next, these models are combined with an image segmentation method to improve the local image quality. This scheme not only keeps an effective control in balance between bitrate and distortion, but also improves the spatial structure of images. Experiments are done both in objective and subjective ways. Results show that after this optimization, LAR has an efficient improvement of subjective image quality of decoded images. This improvement is significantly visible and compared with other compression methods using objective and subjective quality metrics