Algorithms for Manipulating Compressed Images
IEEE Computer Graphics and Applications
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Content-based image enhancement in the compressed domain based on multi-scale α-rooting algorithm
Pattern Recognition Letters
Compressed domain implementation of fuzzy rule-based contrast enhancement
FS'08 Proceedings of the 9th WSEAS International Conference on Fuzzy Systems
WSEAS Transactions on Signal Processing
WSEAS Transactions on Information Science and Applications
3D techniques used for conservation of museum patrimony
WSEAS Transactions on Signal Processing
Filtering vs. nonlinear estimation procedures for image enhancement
WSEAS Transactions on Computers
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In the past few years the resolution of images increased and the requirement for large storage space and fast process, directly in the compressed domain, becomes essential. Fuzzy rule-based contrast enhancement, is a well-known rather simple approach with good visual results. As any fuzzy algorithm, it is by default nonlinear, thus not straightforward applicable on the JPEG bitstream data - zig-zag ordered quantized DCT (Discrete Cosine Transform) coefficients. Because of their nonlinear nature the fuzzy techniques don't have yet a well-defined strategy for their implementation in the compressed domain. In this paper, we propose an implementation strategy suitable for single input - single output Takagi-Sugeno fuzzy systems with trapezoidal shaped input membership function, directly in the JPEG compressed domain. The fuzzy sets parameters are adaptively chosen by analyzing the histogram of the image data in the compressed domain, in order to optimally enhance the image contrast. The fuzzy rule-based algorithm requires some threshold comparisons, for which an adaptive implementation, taking into account the frequency content of each block in the compress domain JPEG image is proposed. This guarantees the minimal error implementation at minimum computational cost.