In this paper, we propose a simple, non iterative blocking artifacts reduction method for block discrete cosine transform (DCT) compressed images, using adaptive bilateral filter. Bilateral filter when applied on a input image, smooths out the blocking artifacts by weighted averaging of the pixel values without smoothing the edges. The proper selection of the bilateral filter parameters is very important and affects the filtering results significantly. We select the bilateral filter parameters optimally, through empirical study. The bilateral filter parameters are made adaptive to different decompressed images using different quantization tables. Our main contribution in this paper is to select the bilateral filter parameters optimally and adaptively through empirical study, in application to image deblocking. The proposed method shows highly encouraging results both objectively and subjectively, when compared to many state of the art image deblocking schemes including a recent method based on adaptive bilateral filter.
I. INTRODUCTIONThe widely used image and video compression standards (e.g.,JPEG, H.26L, MPEG) are based on block based DCT [2], due to its some advantages, like good energy compaction property, simple hardware implementation and low computational complexity. The main problem with the block DCT methods is that the decoded images exhibits annoying blocking artifacts at high compression ratios. To reduce the blocking artifacts, several approaches have been proposed. A 3x3 gaussian filter is applied to the pixels along the block boundaries in [3]. This approach introduces blurring, when the true edges in the image are treated with the above filter. Minami and Zakhor [21] proposed to minimize a criterion called mean squared difference of slope (MSDS) for reducing the blocking artifacts. The projections onto convex sets (POCS) methods [5][6][7][8][22] are iterative in nature and have high computational complexity. The POCS algorithms have shown good results. Wu et al.[9] proposed a wavelet based deblocking scheme based on soft thresholding. Averbuch et al [10] proposed to apply the weighted sums on pixel quartets which are symmetrically aligned to the block boundaries to reduce the blocking artifacts. Xu et al. [11] proposed to reduce the blocking artifacts in discrete hadamard transform (DHT) domain by calculating the blocking activities in the DHT domain to classify the smooth and coarse regions and according to the block activities the blocking artifacts are adaptively filtered.
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