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A Novel DCT-Based Just Noticeable Difference Model via Block Energy

Just noticeable difference (JND), which reflects the minimum visibility threshold of human visual system, is usually utilized to remove the perceptual redundancies for image/video coding. However, most of the existing DCT-based JND models failed to effectively estimate contrast masking (CM) of image blocks with different complexity. In this paper, we propose an improved CM model via frequency energy of DCT block, which is calculated based on DCT coefficient distribution. Then, by integrating luminance adaptation and contrast sensitivity function, an effective JND model in the DCT domain is realized. Experimental results have confirmed that the proposed method can produce more accurate JND threshold and remove more visual redundancies than the state-of-the-art JND models.