公开(公告)号：US20200186836A1

公开(公告)日：2020-06-11

申请号：US16210900

申请日：2018-12-05

Applicant: Google LLC

Inventor： Peyman Milanfar ,  Feng Yang ,  Sungjoon Choi

IPC: H04N19/625 ,  H04N19/124 ,  H04N19/184

Abstract: Methods are provided for sharpening or otherwise modifying compressed images without decompressing and re-encoding the images. An overall image quality is determined based on the source of the compressed image, the quantization table of the compressed image, or some other factor(s), and a set of scaling factors corresponding to the image quality is selected. The selected scaling factors are then applied to corresponding quantization factors of the image's quantization table or other parameters of the compressed image that describe the image contents of the compressed image. The scaling factors of a given set of scaling factors can be determined by a machine learning process that involves training the scaling factors based on training images determined by decompressing and then sharpening or otherwise modifying a source set of compressed images. These methods can provide improvements with respect to encoded image size and computational cost of the image modification method.

公开(公告)号：US11178430B2

公开(公告)日：2021-11-16

申请号：US16210900

申请日：2018-12-05

Applicant: Google LLC

Inventor： Peyman Milanfar ,  Feng Yang ,  Sungjoon Choi

IPC: H04N19/625 ,  H04N19/124 ,  H04N19/184

Abstract: Methods are provided for sharpening or otherwise modifying compressed images without decompressing and re-encoding the images. An overall image quality is determined based on the source of the compressed image, the quantization table of the compressed image, or some other factor(s), and a set of scaling factors corresponding to the image quality is selected. The selected scaling factors are then applied to corresponding quantization factors of the image's quantization table or other parameters of the compressed image that describe the image contents of the compressed image. The scaling factors of a given set of scaling factors can be determined by a machine learning process that involves training the scaling factors based on training images determined by decompressing and then sharpening or otherwise modifying a source set of compressed images. These methods can provide improvements with respect to encoded image size and computational cost of the image modification method.