Method for Determining a Visual Quality Index of a High Dynamic Range Video Sequence

A method for determining a visual quality index of at least one high dynamic range video sequence (HDR sequence), distorted by image processing operations and issued from a reference high dynamic range video sequence, each of the HDR sequence and the reference HDR sequence comprising Nframe video frames t, with N≧2 and tε[1 . . . Nframe], each video frame t comprising a plurality of pixels organized into rows and columns and each pixel having at least a luminance value, the method comprising:

• applying a transformation to the video frames t of the HDR sequence and the reference HDR sequence in order to obtain video frames t of the HDR sequence and the reference HDR sequence in a perceived luminance domain, the transformed luminance values of the video frames tin the perceived luminance domain being substantially linear to the luminance values perceived by the human visual system for the HDR sequence and the reference HDR sequence,
• computing, for each couple of frames t of the HDR sequence and the reference HDR sequence in the perceived luminance domain, Nscale×Norient similarity frames Simt,s,o representative of a perceptual similarity between the frame t of the HDR sequence and the frame t of the reference HDR sequence at different spatial scales s and different spatial orientations o, with sε[1 . . . Nscale] and oε[1 . . . Norient], a similarity value being associated to each pixel of the similarity frame Simt,s,o,
• computing, for each couple of frames t of the HDR sequence and the reference HDR sequence, a global similarity frame Simt based on the computed similarity frames Simt,s,o at the different spatial scales s and the different spatial orientations o,
• pooling, for each group of q consecutive global similarity frames Simt, with q≧2, and for each one of a plurality of spatio-temporal tubes within said group of q consecutive global similarity frames Simt, the similarity values of the pixels included in said spatio-temporal tubes in order to generate a short term error value for each said spatio-temporal tubes, the short term error values of each spatio-temporal tube being included into an error map,
• pooling at least a portion of the short term error values of each error map in order to generate a short term quality score for each group of q consecutive global similarity frames Simt, and
• computing the visual quality index of the HDR sequence based on said short term quality scores.