Resource Efficient Real-Time Processing of Contrast Limited Adaptive Histogram Equalization
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1 Resource Efficient Real-Time Processing of Contrast Limited Adaptive Histogram Equalization Burak Ünal, Ali Akoglu Reconfigurable Computing Lab Department of Electrical and Computer Engineering The University of Arizona 1
2 Outline Motivation Histogram Equalization General Histogram Equalization Adaptive Histogram Equalization Contrast Limited Adaptive Histogram Equalization Related Works State-of-the-art Implementation Contextual CLAHE Histogram Generation Histogram Distribution and CDF Interpolation Technique Testbed Results Conclusion and Future Work 2
3 Motivation Contact Sensing Burdensome Labor-intensive Destructive Non-contact Sensing Structural challenge Sunlight variety Poor image quality How can we enhance the image quality?
4 Histogram Equalization Input Image Image Histogram (a) Histogram Equalization (HE) 4
5 Adaptive Histogram Equalization Input Image (b) Adaptive HE (AHE) (c) Contrast Limited AHE (CLAHE)
6 Adaptive Histogram Equalization Input Image (b) Adaptive HE (AHE) (c) Contrast Limited AHE (CLAHE)
7 Related Works FPGA Based Implementations HE AHE CLAHE General HE Specified HE Partially Overlapped Fully Overlapped HE Specified HE Specified HE 2 AHE CLAHE fps - Missing local details fps - For specific task - 2.5Mpixels - 25 fps - For specific task fps block RAMs - 640x fps - Extremely memory depended (192 BRAM) 7
8 Existing CLAHE Implementation 8
9 Existing CLAHE Implementation Pros: Real-time implementation 537.9fps The speed of algorithm is independent from image size Cons: Requires 192x18K BRAM Larger image size needs 320 BRAM (1920x1080) Consume large amount of logic resource 9
10 Contextual CLAHE 256 x 9 x 640 = KB (HB) 256 x 9 x 257 = K KB (THB) 256 x 13 x 8 = KB 4 row = KB Combine tiles via interpolation. 10
11 Buffer Histogram Generation K K Image β intensity N-1 h k = 255 1, I i = k 0 other k=0 1 9 Histogram BRAM Din Dout 9 Buffer 1/0 Adder Pixel Value 8 8 Address β Comparator Exceed Bin Counter Excess Counter 8 12 excess pixels capacity bins 11
12 Histogram Distribution & CDF (a) histogram cut (b) iteration 1 ( c) iteration 2 (d) iteration n β β β β N-1 intensity α intensity N-1 α intensity N-1 α intensity N-1 (e) CDF CDF = m x,y n = n k=0 h k 1 M N 2 12
13 Interpolation Technique UL UR w z t BL s BR I new = s s + w t z + t m UL n + z z + t m UR n + w s + w t z + t m BL n + z z + t m BR n (3) 13
14 Contextual CLAHE 14
15 YUV to RGB converter HE for Color Image FPGA Input Stream 24 RGB to YUV converter Y U 8 V 8 8 Histogram generation & cutoff Frame Buffer Buffer 8 Histogram distribution & CDF unit Mapping Function Y U 8 24 Output Stream V Y stands for the luma (the brightness). U and V are the chrominance (color) components. 15
16 Testbed 16
17 Histogram Equalization Results (a) Original Image (b) Enhanced Image 17
18 Histogram Equalization Results (a) FPGA (b) Matlab 18
19 Histogram Equalization Results FPGA and Matlab based output comparison with 0.39% difference error rate =
20 Histogram Equalization Results Logic Resource CCLAHE CLAHE Number of Slice Registers Number of Slice LUTs Number of fully used LUT-FF pairs Number of Block RAM/FIFO Operatinal Frequency MHz MHz Performance fps fps Frame Size 512 x x x x 1080 Critical Path Delay ns ns ns ns Maximum Operational Frequency MHZ MHz MHz MHz Performance fps fps fps fps 20
21 Conclusion and Future Work Real-time processing of CLAHE. First implementation of interpolation based Contextual CLAHE. Introduced a method for real time implementation of Contextual CLAHE to solve memory dependency issue. Modified the flow of algorithm for FPGA implementation. Histogram generation method is restructured to reduce block RAM usage. Histogram redistribution technique is proposed to implement iterative redistribution algorithm in hardware. Alternative interpolation calculation method is proposed to the computation complexity. Histogram equalization architecture will be parallelized to increase its performance for larger image size. Investigate different transfer function for calculating CDF. Contrast-sensitive transfer function. 21
22 Q & A 22
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