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A 3D mesh can be subjected to different types of operations, such as compression, watermarking etc. Such processes lead to geometric distortions compared to the original version. In this context, quantifying the resultant modifications to the original mesh and evaluating the perceptual quality of degraded meshes become a critical issue. The perceptual 3D meshes quality is central in several applications to preserve the visual appearance of these treatments. The used metrics results have to be well correlated to the visual perception of humans. Although there are objective metrics, they do not allow the prediction of the perceptual quality, and do not include the human visual system properties. In the current work, a comparative study between the perceptual quality assessment metrics for 3D meshes was conducted. The experimental study on subjective database published by LIRIS / EPFL was used to test and to validate the results of six metrics. The results established that the Mesh Structural Distortion Measure metric achieved superior results compared to the other metrics.

For communication and storage efficiency, image data should be substantially compressed. The compression ratio is limited by noise, which degrades the correlation between pixels. Noise can occur during image capture, transmission or processing, and may be dependent on or independent of image content. In this study, we use standardfilters that permits to remove some details of the image and to reduce all possible noise. After filtering, the image is compressed with JPEG2000. By discarding the noise, the compression ratio can be improved. This method was verified using 30 images. This technique can increase the ratio without significantly affecting the image quality. This process will have a great impact on storage and transmission.