METHODS FOR DYNAMICALLY SELECTING COMPRESSION METHOD FOR GRAPHICS REMOTING

• US 20100254622A1
• Filed: 04/06/2009
• Published: 10/07/2010
• Est. Priority Date: 04/06/2009
• Status: Active Grant

• Current Assignee: Red Hat Israel Ltd. (International Business Machines Corporation)
• Original Assignee: Red Hat Israel Ltd. (International Business Machines Corporation)
• Inventors: Halperin, Yonit Tova, KAMAY, YANIV
• Granted Patent: US 9,025,898 B2
• Time in Patent Office: Days
• US Class Current: 382/239
• CPC Class Codes: H04N 19/115 Selection of the code volume for a coding unit prior to coding
• CPC Class Codes: H04N 19/12 Selection from among a plurality of transforms or standards, e.g. selection between discrete cosine transform [DCT] and sub-band transform or selection between H.263 and H.264
• CPC Class Codes: H04N 19/136 Incoming video signal characteristics or properties
• CPC Class Codes: H04N 19/27 involving both synthetic and natural picture components, e.g. synthetic natural hybrid coding [SNHC]
• CPC Class Codes: H04N 21/23418 involving operations for analysing video streams, e.g. detecting features or characteristics television picture signal circuitry for scene change detection H04N5/147; filtering for image enhancement G06T5/00; methods or arrangements for recognising scenes G06V20/00; arrangements characterised by components specially adapted for monitoring, identification or recognition of video in broadcast systems H04H60/59
• CPC Class Codes: H04N 21/2343 involving reformatting operations of video signals for distribution or compliance with end-user requests or end-user device requirements video transcoding H04N19/40; media packet handling at the source H04L65/762
• CPC Class Codes: H04N 21/8146 involving graphical data, e.g. 3D object, 2D graphics

Abstract

Method and apparatus for improving compression efficiency of for graphics remoting are described herein. According to one embodiment, for each data object of a stream generated within a virtual machine, the data object including graphics data representing an image to be rendered at a client over a network, it is determined whether an image associated with each data object is related to a real life content or an artificial content based on a similarity of one or more pixels selected within at least a segment of the image. A compression method is selected based on the determination of whether the image is related to a real life content or an artificial content. The image is compressed using the selected compression method and thereafter, the compressed image is streamed to the client over the network to be rendered at the client. Other methods and apparatuses are also described.

Claims

1. A computer-implemented method, comprising:

for each data object of a stream, determining whether an image associated with each data object is related to a real life content or an artificial content based on a similarity of one or more pixels selected within at least a segment of the image; and

compressing the image using a compression method selected based on the determination of whether the image is related to a real life content or an artificial content.

2. The method of claim 1, further comprising streaming the compressed image to a client over a network to be rendered at the client.

3. The method of claim 1, wherein the data object includes graphics data representing the image to be rendered at a client over a network.

4. The method of claim 1, wherein determining whether the image is associated with a real life content or an artificial content comprises:

for each selected pixel of the at least a segment of the image, calculating a score representing a similarity between the pixel and its one or more surrounding pixels; and

calculating an average score for the selected pixels of at least a segment of the image, wherein the average score is used to determine whether the image is associated with a real life content or an artificial content.

5. The method of claim 4, further comprising:

for each selected pixel, assigning an individual score to one or more adjacent pixels based on a difference between pixel values of a current pixel and the one or more adjacent pixels; and

calculating a final score for the current pixel based on individual scores of the one or more adjacent pixels of the current pixel.

6. The method of claim 5, further comprising:

assigning a first score having a zero value if the pixel values between the current pixel and an adjacent pixel are identical;

assigning a second score having a predetermined positive value if the difference between the pixel values of the current pixel and the adjacent pixel exceeds a predetermined threshold; and

assigning a third score having a predetermined negative value if the difference between the pixel values of the current pixel and the adjacent pixel is below the predetermined threshold.

7. The method of claim 4, further comprising:

selecting a first compression method for compressing the image if the average score is below a predetermined threshold; and

selecting a second compression method for compressing the image if the average score exceeds the predetermined threshold, the second compression method being different than the first compression method.

8. The method of claim 1, wherein the image is one of virtual desktop images in the stream to be rendered at the client as part of a virtual desktop environment, wherein the stream of virtual desktop images are generated from a desktop application executed within a virtual (VM) and accessed remotely by the client over the network.

9. The method of claim 8, wherein the desktop application is executed within a guest operating system (OS) within the VM, and wherein the guest OS is managed by a host OS which virtualizes underlying hardware to the guest OS.

10. The method of claim 9, wherein the guest OS is running as a process in a user space of the host OS, wherein the host OS comprises a kernel module running within a kernel space of the host OS which enables the host OS to be a hypervisor for managing the VM, and wherein the guest OS comprises a hardware emulator for emulating the underlying hardware which is exposed by the kernel module.

11. A computer readable storage medium including instructions that, when executed by a processing system, cause the processing system to perform a method comprising:

for each data object of a stream, determining whether an image associated with each data object is related to a real life content or an artificial content based on a similarity of one or more pixels selected within at least a segment of the image; and

compressing the image using a compression method selected based on the determination of whether the image is related to a real life content or an artificial content.

12. The computer readable storage medium of claim 11, wherein the method further comprises:

streaming the compressed image to a client over a network to be rendered at the client.

13. The computer readable storage medium of claim 11, wherein determining whether the image is associated with a real life content or an artificial content comprises:

for each selected pixel of the at least a segment of the image, calculating a score representing a similarity between the pixel and its one or more surrounding pixels; and

calculating an average score for the selected pixels of the at least a segment of the image, wherein the average score is used to determine whether the image is associated with a real life content or an artificial content.

14. The computer readable storage medium of claim 11, wherein the method further comprises:

for each selected pixel, assigning an individual score to one or more adjacent pixels based on a difference between pixel values of a current pixel and the one or more adjacent pixels; and

calculating a final score for the current pixel based on individual scores of the one or more adjacent pixels of the current pixel.

15. The computer readable storage medium of claim 14, wherein the method further comprises:

assigning a first score having a zero value if the pixel values between the current pixel and an adjacent pixel are identical;

assigning a second score having a predetermined positive value if the difference between the pixel values of the current pixel and the adjacent pixel exceeds a predetermined threshold; and

assigning a third score having a predetermined negative value if the difference between the pixel values of the current pixel and the adjacent pixel is below the predetermined threshold.

16. The computer readable storage medium of claim 12, wherein the method further comprises:

selecting a first compression method for compressing the image if the average score is below a predetermined threshold; and

selecting a second compression method for compressing the image if the average score exceeds the predetermined threshold, the second compression method being different than the first compression method.

17. The computer readable storage medium of claim 13, wherein the image is one of virtual desktop images in the stream to be rendered at the client as part of a virtual desktop environment, wherein the stream of virtual desktop images are generated from a desktop application executed within a virtual (VM) and accessed remotely by the client over the network.

18. The computer readable storage medium of claim 17, wherein the desktop application is executed within a guest operating system (OS) within the VM, and wherein the guest OS is managed by a host OS which virtualizes underlying hardware to the guest OS.

19. The computer readable storage medium of claim 18, wherein the guest OS is running as a process in a user space of the host OS, wherein the host OS comprises a kernel module running within a kernel space of the host OS which enables the host OS to be a hypervisor for managing the VM, and wherein the guest OS comprises a hardware emulator for emulating the underlying hardware which is exposed by the kernel module.

20. A data processing system, comprising:

a processor;

a memory;

a virtual machine (VM) executed from the memory to virtualize the processor and memory;

a guest operating system (OS) executed within the VM, the guest OS including a desktop application running therein to generate a stream of data objects, each including graphics data representing an image to be rendered at a client over a network, and

a remote display system coupled to the VM, the remote display system including

a content classifier, for each data object, to determine an image associated with each data object whether the image is related to a real life content or an artificial content based on a similarity of pixels within at least a segment of the image, and

a data compressor to select a compression method based on the determination of whether the image is related to a real life content or an artificial content and to compress the virtual desktop image using the selected compression method.

21. The data processing system of claim 20, wherein for each selected pixel of the at least a segment of the image, the content classifier is configured to calculate a score representing a similarity between the selected pixel and its one or more surrounding pixels and to calculate an average score for the selected pixels of the at least a segment of the image, wherein the average score is used to determine whether the image is associated with a real life content or an artificial content.