Cameras, especially cameraphones, are using a large panel of technologies, such as multi-frame stacking and local tone mapping to capture and render scenes with high dynamic range. ISO defined charts for OECF estimation and visual noise measurement are not really designed for these specific use cases, especially when no manual control of the camera is available. Moreover, these charts are limited to one measurement. We developed a versatile laboratory setup to evaluate image quality attributes, like autofocus, exposure and details preservation. It is tested in various lighting conditions, with several dynamic ranges up to 7EV difference within the scene, under different illuminants. Latest visual noise measurements proposed by IEEE P1858 or ISO-15739 are not giving fully satisfactory results on our laboratory scene, due to differences in the chart, framing and lighting conditions used. We performed subjective visual experiments to build a quality ruler of noisy grey patches, and use it as a dataset to develop and validate an improved version of a visual noise measurement. In the experiments we also studied the impact of different environment conditions of the grey patches to assess their relevance to our algorithm. Our new visual noise measurement uses a luminance sensitivity function multiplied by the square root of the weighted sum of the variances of the Lab coordinates of the patches. A non-linear JND scaling is applied afterwards to get a visual noise measurement in units of JND of noisiness.