Method of decoding a current image

Abstract

The present invention relates to an image processing technique, and in particular to a method for restoring a compressed image by using a hybrid motion compensation discrete cosine transform (hybrid MC / DCT) mechanism, including: a step of defining a smoothing functional having a smoothing degree of an image and reliability for an original image by pixels having an identical property in image block units; and a step of computing a restored image by performing a gradient operation on the smoothing functional in regard to the original image, thereby preventing the blocking artifacts and the ringing effects in regard to the pixels having an identical property in image blocks.In one embodiment, the method includes obtaining a pixel value in a current block and at least one adjacent pixel value, obtaining a difference value between the pixel value in the current block and the adjacent pixel value, and obtaining a smoothing value of the current image based on the difference value. A pixel value around a boundary of the block is smoothed based on a threshold value and the smoothing value.

Description

DIVISIONAL REISSUE APPLICATIONS[0001]Notice: More than one reissue application has been filed for the reissue of U.S. Pat. No. 6,611,361. The other reissue applications are application Ser. Nos. 11 / 212,137, 11 / 808,423, 11 / 892,177, 11 / 892,178, and 11 / 892,179. <?insert-end id="INS-S-00002" ?>DOMESTIC PRIORITY INFORMATION[0002]This is a direct divisional of application Ser. No. 11 / 212,137, filed Aug. 26, 2005; the entire contents of which are hereby incorporated by reference.<?insert-end id="INS-S-00003" ?>BACKGROUND OF THE INVENTION[0003]1. Field of the Invention[0004]The present invention relates to an image process technique, and in particular to a method for restoring a compressed image by using a hybrid motion compensation discrete cosine transform (hybrid MC / DCT) mechanism, and an apparatus therefor.[0005]2. Description of the Background Art[0006]In general, image compression techniques, such as MPEG1 and MPEG2 employ a hybrid motion compensation discrete cosine trans...

AI Technical Summary

Benefits of technology

The present invention provides a method for restoring a compressed image of an image processing system that reduces blocking artifacts and ringing effects in the restored image signal. The method takes into account the smoothing degree of the image and the reliability of the original image by pixels having an identical property in image block units during the decoding process. The method includes obtaining a pixel value in a current block and at least one adjacent pixel value, obtaining a difference value between the pixel value in the current block and the adjacent pixel value, and obtaining a smoothing value of the current image based on the difference value. The pixel value around a boundary of the block is smoothed based on a threshold value and the smoothing value.

Problems solved by technology

However, information of the original image signal is lost during the process of coding the image signal described above, especially during the quantization process, thereby causing blocking artifacts and ringing effects to the image which is reconstructed in the decoder.

The blocking artifacts imply irregularity between the blocks generated due to information loss resulting from the quantization of the low-frequency DCT coefficients, and the ringing effects result from quantization errors of the high-frequency DCT coefficients.

The DCT does not consider the correlation between the blocks, and quantizes the low-frequency elements by blocks, thereby destroying continuity of the adjacent blocks.

The ringing effects generated by increasing the quantization interval are serious especially in a contour of an object in the reconstructed image.

However, an adaptive processing power in accordance with a quantization parameter is deficient, and thus a screen quality of the restored image is excessively smoothed according to the kind of the images and compression ratio.

However, the computed values form a matrix shape, and thus a real time processing is difficult due to the great computation amount.

Thus, the system is not adaptive.

Also, the information in the temporal section is not processed, and thus irregularity between the images cannot be adaptively processed.

Images