Abstract
For the requirement of quality-based image coding, an approach to predict the quality of image coding based on differential information entropy is proposed. First of all, some typical prediction approaches are introduced, and then the differential information entropy is reviewed. Taking JPEG2000 as an example, the relationship between differential information entropy and the objective assessment indicator PSNR at a fixed compression ratio is established via data fitting, and the constraint for fitting is to minimize the average error. Next, the relationship among differential information entropy, compression ratio and PSNR at various compression ratios is constructed and this relationship is used as an indicator to predict the image coding quality. Finally, the proposed approach is compared with some traditional approaches. From the experiments, it can be seen that the differential information entropy has a better linear relationship with image coding quality than that with the image activity. Therefore, the conclusion can be reached that the proposed approach is capable of predicting image coding quality at low compression ratios with small errors, and can be widely applied in a variety of real-time space image coding systems for its simplicity.
Highlights
With the gradual reduction of the Earth’s resources, countries all over the world are becoming increasingly aware of the importance of exploiting space resources
The relationship between the image coding performance and the image activity at fixed compression ratios was established in previous researches [7,8,9], and is given as follows: PSNR |CR f ( image activity measure (IAM) ) ln( IAM )
We find out that for some images, the relationship between the image activity and PSNR is not that close
Summary
With the gradual reduction of the Earth’s resources, countries all over the world are becoming increasingly aware of the importance of exploiting space resources. The target is to provide accurate service for sectors of land, environment and agriculture, etc In all these projects, observing images is an efficient way for the acquisition of space information. A lot of research has been done on the rate control algorithms in JPEG2000 [4,5,6] These algorithms consume large amounts of memory and computing time for the reason that most of the coding process must be performed in order to estimate the image distortion. Differential information entropy is used to predict the image coding quality at low compression ratios. Taking the JPEG2000 coding algorithm as an example, the relationship between the differential information entropy and the objective assessment indicator (Peak Signal-to-Noise Ratio—PSNR) at fixed compression ratios is established through data fitting.
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