Computationally efficient algorithm for fuzzy rule-based enhancement on JPEG compressed color images

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. Key-Words: Compressed domain processing, Discrete Cosine Transform (DCT), nonlinear operation, fuzzy rule-based contrast enhancement, fuzzy sets, color image enhancement.