论文标题
基于对象检测的变量量化处理
Object Detection-Based Variable Quantization Processing
论文作者
论文摘要
在本文中，我们为常规图像和视频编码器提出了一种预处理方法，该方法可以使这些现有的编码者了解内容。通过遍历我们的过程，可以在传统编码器上设置更高质量的参数，而不会增加输出尺寸。静止框架或图像将首先通过对象检测器。检测结果的属性将决定以下过程的参数，或者如果在给定帧中未检测到对象，则将绕过系统。处理方法利用自适应量化过程来确定要删除的数据部分。该方法主要基于JPEG压缩理论，对于基于JPEG的编码器，例如JPEG编码器和Motion JPEG编码器，非常适合。但是，MPEG第2部分，H.264等基于DCT的编码器也可以从此方法中受益。在实验中，我们比较了在相同的比特率和相似的MS-SSIM下的MS-SSIM，但比特率增强了。由于这种方法基于人类的看法，即使使用类似的MS-SSIM，总体观看体验将比直接编码的体验更好。
In this paper, we propose a preprocessing method for conventional image and video encoders that can make these existing encoders content-aware. By going through our process, a higher quality parameter could be set on a traditional encoder without increasing the output size. A still frame or an image will firstly go through an object detector. Either the properties of the detection result will decide the parameters of the following procedures, or the system will be bypassed if no object is detected in the given frame. The processing method utilizes an adaptive quantization process to determine the portion of data to be dropped. This method is primarily based on the JPEG compression theory and is optimum for JPEG-based encoders such as JPEG encoders and the Motion JPEG encoders. However, other DCT-based encoders like MPEG part 2, H.264, etc. can also benefit from this method. In the experiments, we compare the MS-SSIM under the same bitrate as well as similar MS-SSIM but enhanced bitrate. As this method is based on human perception, even with similar MS-SSIM, the overall watching experience will be better than the direct encoded ones.
