Computer Vision News - October 2021
3 Summary 5 Removing Diffraction Image Artifacts in ... The degradation model is described as: where x represents the real scene irradiance that has a high dynamic range (HDR), k is the known convolution kernel (PSF), denotes the 2D convolution operator, and n models the camera noise. C(·) is a clipping operation with a set threshold and φ(·) is a non-linear tone mapping. These two elements add a saturation effect derived from the limited dynamic range of digital sensors and make the model closer to the human perception of the scene. The second element in the paper consists in defining the PSF. This can be simulated but it was found that the real-measured PSF slightly differs in colours and contrast due to model approximations and manufacturing imperfections. The first contribution consists in the formulation of an image formation model for UDC systems which considers dynamic range and saturation and could simulate more complex and realistic degradation compared to the State-of-the-Art. ̂ = [ ( ∗ + )] ̂ = [ ( ∗ + )] Hence, the authors measure the real-word PSF by placing a white point light source 1-meter away from the OLED display. The PSF is used as part of a model-based data synthesis pipeline to generate realistic degraded images. To do this, the objects considered are real scenes with high dynamic range. This is essential because 1) the spike-shaped sidelobes (typical of the PSF) can be amplified to be visible (flares) in the degraded image, and 2) due to the high dynamic range of the input scene, the digital sensor (usually 10-bit) will inevitably get saturated in real applications, resulting in an information loss. Hence, images captured by UDC systems in real scenes will exhibit structured flares near strong light sources. The previous imaging system, however, cannot model this degradation, because it captures images displayed on an LCD monitor, which commonly has limited dynamic range. This is shown below, where is demonstrated that the real HDR scene captured by the
Made with FlippingBook
RkJQdWJsaXNoZXIy NTc3NzU=