Abstract: A method of operating a Solid-State Drive (SSD) includes determining optimized thresholds of each corresponding segments according to their frequency of use, and executing a flush operation to write the one of the corresponding segments into a memory device according to the optimized thresholds of the corresponding segments.

Abstract: A method of operating a Solid-State Drive (SSD) includes determining optimized thresholds of each corresponding segments according to their frequency of use, and executing a flush operation to write the one of the corresponding segments into a memory device according to the optimized thresholds of the corresponding segments

Abstract: A loop filtering method based on an adaptive self-guided filtering is mainly an adaptive self-guided filtering technology considering local structure information of an image, wherein a regularization coefficient is adjusted by calculating a weight coefficient of the regularization coefficient to realize the adaptive self-guide filtering, and then a region-level subspace mapping iterative optimization implemented on each region enables a mapping result of the each region to be optimal, wherein the mapping result of a whole image is closer to an original image. Beneficial effects of the loop filtering method are as follows: a filtering effect of a loop filtering is improved, a distortion effect of a reconstruction image is reduced and a reconstruction quality of a video frame is improved, wherein the reconstruction image is more favorable for a subsequent reference and a subjective and objective quality of the video is further improved.

Abstract: A flush method of a solid-state drive (SSD) comprises mapping a group of data to multiple segments of a mapping table; generating a recording table for recording a total value and multiple count values corresponding to the multiple segments; when one of the data is written, increasing one of the multiple count values corresponding to one of the multiple segments of the one of the data by a number, and increasing the total value by another number; determining whether the one of the multiple count values is greater than one of multiple optimized thresholds corresponding to the one of the multiple count values; and executing a flush operation to write the one of the multiple segments into a memory and restoring the mapping table if the one of the multiple count values is greater than the one of the multiple optimized thresholds.

Abstract: A temporal domain rate distortion optimization considering a coding-mode adaptive distortion propagation is provided. A problem of dependency rate distortion optimization based on a temporal domain distortion propagation is induced again according to a temporal domain dependency relationship under an LD structure and a distortion propagation analysis under a skip mode and an inter mode; and an aggregation distortion of a current coding unit and an affected future coding unit are estimated and a propagation factor of a coding unit in a temporal domain distortion propagation model is calculated by constructing a time propagation chain, wherein a Lagrange multiplier is adjusted through an accurate propagation factor to realize a temporal domain dependency rate distortion optimization, and an I frame is subjected to a secondary coding technology to realize the temporal domain dependency rate distortion optimization of the I frame.

Abstract: A temporal domain rate distortion optimization considering a coding-mode adaptive distortion propagation is provided. A problem of dependency rate distortion optimization based on a temporal domain distortion propagation is induced again according to a temporal domain dependency relationship under an LD structure and a distortion propagation analysis under a skip mode and an inter mode; and an aggregation distortion of a current coding unit and an affected future coding unit are estimated and a propagation factor of a coding unit in a temporal domain distortion propagation model is calculated by constructing a time propagation chain, wherein a Lagrange multiplier is adjusted through an accurate propagation factor to realize a temporal domain dependency rate distortion optimization, and an I frame is subjected to a secondary coding technology to realize the temporal domain dependency rate distortion optimization of the I frame.

Abstract: A loop filtering method based on an adaptive self-guided filtering is mainly an adaptive self-guided filtering technology considering local structure information of an image, wherein a regularization coefficient is adjusted by calculating a weight coefficient of the regularization coefficient to realize the adaptive self-guide filtering, and then a region-level subspace mapping iterative optimization implemented on each region enables a mapping result of the each region to be optimal, wherein the mapping result of a whole image is closer to an original image. Beneficial effects of the loop filtering method are as follows: a filtering effect of a loop filtering is improved, a distortion effect of a reconstruction image is reduced and a reconstruction quality of a video frame is improved, wherein the reconstruction image is more favorable for a subsequent reference and a subjective and objective quality of the video is further improved.

Abstract: A flush method of a solid-state drive (SSD) comprises mapping a group of data to multiple segments of a mapping table; generating a recording table for recording a total value and multiple count values corresponding to the multiple segments; when one of the data is written, increasing one of the multiple count values corresponding to one of the multiple segments of the one of the data by a number, and increasing the total value by another number; determining whether the one of the multiple count values is greater than one of multiple optimized thresholds corresponding to the one of the multiple count values; and executing a flush operation to write the one of the multiple segments into a memory and restoring the mapping table if the one of the multiple count values is greater than the one of the multiple optimized thresholds.