Research on Webp Image Compression Format Based on VP8 Encoding

With the sharp increase in consumer demand and multimedia entertainment, the previous generation of Internet standards and video solutions have been unable to meet the high-speed growth of high-definition video transmission requirements. In this context, the next-generation Internet solution for future needs-HTML 5 network The development standard and WebM VP8 video compression format came into being. VP8 encoding has extremely high compression ratio and compression quality, and the new picture compression format Webp based on VP8 encoding also has a higher compression rate than JPEG pictures.

1 PSNR and SSIM image quality test standards

1.1 Peak signal-to-noise ratio

PSNR (Peak Signal to Noise RaTIo) is a term indicating the ratio between the maximum power of a signal and the noise power that affects it. It is usually expressed in logarithmic decibels. PSNR is often used as a signal reconstruction measurement in the field of image compression. It is defined by Mean Square Error (MSE). The two M & TImes; N monochrome images I and K, if the noise is similar, then their MSE is defined as:

The peak signal-to-noise ratio is defined as:

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Among them amax = 2k-1, k often takes 8. Both PSNR and MSE perform statistical and average calculations based on pixel gray values, ignoring the effect of the image on the human eye, so they cannot fully reflect the image quality.

1.2 Structural similarity

The pixels of the image are related, and this correlation contains the structural information of the image. SSIM (Structural Similarity Index) is an index that measures the similarity of two images. The distortion SSIM of the original image block x and the distorted image block y is modeled as a combination of three components: brightness l (x, y), contrast c (x, y) and structural information s (x, y):

SSIM (x, y) = l (x, y) · c (x, y) · s (x, y) (3)

Brightness, contrast, and structural information are quantities related to the mean values ​​of x and y μx, μy, standard deviations σx, σy, or covariance σxy, and their expressions are:

C1, C2, and C3 are small constants added to avoid the denominator being zero. When judging the image quality with SSIM, first divide the image into overlapping or non-overlapping sub-blocks of equal size (generally 8 & TImes; 8 size), then use formula (3) to calculate the SSIM value of each sub-block, and then use all the sub-blocks The average value of the block SSIM values ​​is used as a measure of the quality of the entire image. The higher the SSIM value, the higher the similarity between the distorted image and the original image, and the higher the quality of the distorted image.

2 Comparison of PSNR and SSIM of VP8 encoded and X.264 encoded images

Google acquired On2 technology company and then opened the source code of its own VP8 encoding technology. New technologies adopted by VP8 include: advanced prediction coding based on virtual reference frames, multi-threading technology based on macroblock level, improved local reference coding, advanced context entropy coding with increased complexity, adaptive loop filtering for sparse target areas, etc. So that it can be provided with less data

For higher quality videos.

Google claims that VP8 can provide better picture quality than the popular X.264 at the same bit rate, or use less bandwidth under the same picture quality. The X.264 encoding is now the most popular encoding technology, which belongs to the MPEG high-definition encoding part and is a highly compressed digital video codec standard. Both codes are now supported by a large number of manufacturers.

Use representative video scenes to test the performance of two different encoding techniques on video compression and restoration quality. Test videos of scenes with different depth of field are shown in Figure 1. The test video was encoded with Handbrake in X.264 encoding and FFmpeg 0.6 in VP8 format. Then use the MSU MQVT software to test the PSNR and SSIM of the scene. The PSNR data of the test video and the SSIM data of the test video are shown in Figure 2 and Figure 3.

Through the comparison and analysis of software testing, it can be seen that the video quality of VP8 encoding is not much different from X.264. In some scenes, the high-quality encoded X.264 image is slightly better than VP8 encoding, but the video size of VP8 encoding is slightly smaller than X.264. VP8 encoding has just been open source, there is no very mature codec, and it can not be compared with the X.264 encoder developed over the years, but the above test results show that VP8 encoding has a lot of room for development.

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