Publication: Mecanismos de optimización en el procesado para H.265/HEVC
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2016
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Barrio García, Alberto de
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Abstract
En esta memoria se ha implementado una etapa de preprocesado que sirva como primera fase en el proceso de codificación de vídeo. Esta etapa integra dos variedades del filtro de mediana (3×3 y 5×5) y un operador. Dicho operador lleva a cabo el cálculo del gradiente de los píxeles que conforman una imagen o fotograma con objeto de filtrar después aquellos que están por debajo de un determinado valor (threshold). El cálculo de dicho threshold se realiza de manera empírica mediante dos procesos distintos. En el primero se obtienen valores de luminancia y crominancia de píxeles que integran bordes para encontrar aquel que tenga el valor mínimo, mientras que en el segundo se calcula la tasa de píxeles que forman parte de bordes. Una vez se ha realizado el cálculo anterior, se han utilizado distintos valores de threshold, distintas variedades de filtro de mediana y distintos valores de QP (calidad) con objeto de parametrizar las codificaciones que hacen uso de esta nueva etapa. Posteriormente a dichas codificaciones, se han obtenido los tamaños de los bitstreams de salida y se ha evaluado la calidad de los vídeos decodificados o reconstruidos mediante dos métricas objetivas: PSNR y SSIM. Las codificaciones que no utilizan etapa de preprocesado también han sido evaluadas mediante dichas métricas y comparadas con aquellas que sí integran dicha etapa. Los resultados obtenidos dejan patente el compromiso existente entre tamaño de bitstream y calidad, siendo más representativos los de la métrica SSIM, estando esta última más relacionada con la percepción de la imagen por parte del HVS (sistema visual humano). Como resultado, se obtiene para esta métrica tasas de compresión mayores que las alcanzadas sin preprocesamiento, con pérdidas de calidad prácticamente inapreciables.
This MSc Thesis has implemented a preprocessing stage to work as a first step in the process of encoding videos. This stage integrates two varieties of median filter (3×3 and 5×5) and an operator. Such operator performs the calculation of the gradient of the pixels that compose an image or frame in order to filter those below a certain value (threshold). The calculation of this threshold is empirically performed by two different processes. The first one, deals with the luminance and chrominance pixel values that belong to boundaries in order to find the one with the minimum value. On the other hand, the second process is based on the estimation of the pixel rate just considering edge areas. Once the aforementioned calculation has been done, different threshold values, parameters as well as varieties of filters are applied to produce the video encoding. After performing the encoding, the bitstream sizes have been obtained and the quality of the decoded or reconstructed videos has been evaluated using two objective metrics: PSNR and SSIM. The encodings that do not use a preprocessing stage have also been evaluated with these metrics and compared with those that do integrate this stage. The results clearly demonstrate the existence of a trade-off between size and quality bitstream, especially when considering the evaluation with the SSIM metric, as it is more related with the perception of the image by the Human View System. To conclude, the main contribution of this MSc Thesis is the achievement of higher compression rate with a negligible quality loss, in comparison with the conventional video coding processing scheme.
This MSc Thesis has implemented a preprocessing stage to work as a first step in the process of encoding videos. This stage integrates two varieties of median filter (3×3 and 5×5) and an operator. Such operator performs the calculation of the gradient of the pixels that compose an image or frame in order to filter those below a certain value (threshold). The calculation of this threshold is empirically performed by two different processes. The first one, deals with the luminance and chrominance pixel values that belong to boundaries in order to find the one with the minimum value. On the other hand, the second process is based on the estimation of the pixel rate just considering edge areas. Once the aforementioned calculation has been done, different threshold values, parameters as well as varieties of filters are applied to produce the video encoding. After performing the encoding, the bitstream sizes have been obtained and the quality of the decoded or reconstructed videos has been evaluated using two objective metrics: PSNR and SSIM. The encodings that do not use a preprocessing stage have also been evaluated with these metrics and compared with those that do integrate this stage. The results clearly demonstrate the existence of a trade-off between size and quality bitstream, especially when considering the evaluation with the SSIM metric, as it is more related with the perception of the image by the Human View System. To conclude, the main contribution of this MSc Thesis is the achievement of higher compression rate with a negligible quality loss, in comparison with the conventional video coding processing scheme.
Description
Máster en Investigación en Informática, Facultad de Informática, Departamento de Arquitectura de Computadores y Automática, curso 2015-2016