Quantitative visual perception quality measurement for virtual desktops

A non-transitory computer readable storage medium comprising one or more sequences of instructions, the instructions when executed by one or more processors causing the one or more processors to execute the operations of:

• obtaining a set of reference virtual desktop images including one or more of desktop background images, text, icons, windows, or menus;
• generating distorted versions of the reference virtual desktop images that have been distorted by processes involved in remoting a graphical user interface of the virtual desktop;
• receiving a set of subjective visual quality ratings corresponding to the distorted versions of the reference virtual desktop images;
• training a linear fusion model using as input the set of reference virtual desktop images, the distorted versions and the set of subjective visual quality ratings to determine a set of weightings, wherein the linear fusion model combines a peak signal to noise ratio (PSNR) score, a structural similarity (SSIM) score and a feature similarity (FSIM) score according to the determined weightings;
• receiving a distorted image of a virtual desktop interface displayed by a remote server, the distorted image received by a client device from the remote server over a network connection;
• displaying the distorted image of the virtual desktop interface by the client device and capturing a screenshot of the distorted image;
• comparing the screenshot of the distorted image to a distortion-free reference image by the client device;
• and
• computing a visual quality metric for the screenshot of the distorted image using the trained linear fusion model, wherein resource allocation for hosting the virtual desktop is adjusted based at least in part on the visual quality metric.

A computing device, comprising:

• one or more processors;
• and
• memory including instructions that when executed by the one or more processors, cause the computing device to:
• obtain a set of reference virtual desktop images including one or more of desktop background images, text, icons, windows, or menus;
• generate distorted versions of the reference virtual desktop images that have been distorted by processes involved in remoting a graphical user interface of the virtual desktop;
• receive a set of subjective visual quality ratings corresponding to the distorted versions of the reference virtual desktop images;
• train a linear fusion model using as input the set of reference virtual desktop images, the distorted versions and the set of subjective visual quality ratings to determine a set of weightings, wherein the linear fusion model combines a peak signal to noise ratio (PSNR) score, a structural similarity (SSIM) score and a feature similarity (FSIM) score according to the determined weightings;
• receive a distorted image of a virtual desktop interface displayed by a remote server, the distorted image received by a client device from the remote server over a network connection;
• display the distorted image of the virtual desktop interface by the client device and capturing a screenshot of the distorted image;
• compare the screenshot of the distorted image to a distortion-free reference image by the client device;
• and
• compute a visual quality metric for the screenshot of the distorted image using linear fusion model, wherein resource allocation for hosting the virtual desktop is adjusted based at least in part on the visual quality metric.