This work presents a no-reference image sharpness metric based on human blur perception for JPEG2000 compressed image. The metric mainly uses a ringing measure. And a blurring measure is used for compensation when the blur is so severe that ringing artifacts are concealed. We used the anisotropic diffusion for the preliminary ringing map and refined it by considering the property of ringing structure. The ringing detection of the proposed metric does not depend on edge detection, which is suitable for high degraded images. The characteristics of the ringing and blurring measures are analyzed and validated theoretically and experimentally. The performance of the proposed metric is tested and compared with that of some existing JPEG2000 sharpness metrics on three widely used databases. The experimental results show that the proposed metric is accurate and reliable in predicting the sharpness of JPEG2000 images. 1. Introduction Images are usually degraded by various factors such as defocusing and compression. Thus, it is more and more necessary to assess the image quality. The most reliable approach of image quality assessment is in the subjective way. The mean opinion score method is commonly used. It is implemented by subjective rating followed by some statistical processes to derive the mean opinion score (MOS). However, the subjective assessment is time-consuming, costly, and impractical. Hence, recently, there has been an increasing interest from the research community and industry towards developing objective assessment techniques. The objective metrics can be divided into three categories: full reference (FR), reduced reference (RR), and no reference (NR) [1]. FR utilizes all information of the reference image while RR uses the detected features. However, the reference image or its features cannot be obtained sometimes. NR needs no reference information. It is widely used and challenging. As the data volume is increasing apace, the limitation of the bandwidth becomes critical. It is more necessary to compress images. Different compression techniques introduce very different distortions. The discrete cosine transform (DCT) [2] based techniques, for example, JPEG and MPEG, lead to blockiness, whereas the JPEG2000 compression [3, 4] involving wavelet transform [5] mainly introduces blurring and ringing artifacts [6]. The particular interest of this work is NR sharpness assessment for JPEG2000 compressed images. The existing metrics for JPEG2000 images can be generally classified into two categories. The first category is about metrics on general
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