A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
LCIS: a boundary hierarchy for detail-preserving contrast reduction
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
The Quotient Image: Class-Based Re-Rendering and Recognition with Varying Illuminations
IEEE Transactions on Pattern Analysis and Machine Intelligence
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
What is the set of images of an object under all possible lighting conditions?
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Lambertian Reflectance and Linear Subspaces
Lambertian Reflectance and Linear Subspaces
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
The CMU Pose, Illumination, and Expression Database
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Smoothing via Contextual and Local Discontinuities
IEEE Transactions on Pattern Analysis and Machine Intelligence
An image preprocessing algorithm for illumination invariant face recognition
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Brightness perception, dynamic range and noise: a unifying model for adaptive image sensors
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Face recognition under varying lighting conditions using self quotient image
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Face recognition under variable lighting using harmonic image exemplars
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Eigenspace-based face recognition: a comparative study of different approaches
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Properties and performance of a center/surround retinex
IEEE Transactions on Image Processing
A multiscale retinex for bridging the gap between color images and the human observation of scenes
IEEE Transactions on Image Processing
Adaptive wavelet thresholding for image denoising and compression
IEEE Transactions on Image Processing
Segmenting focused objects based on the Amplitude Decomposition Model
Pattern Recognition Letters
A sub-block-based eigenphases algorithm with optimum sub-block size
Knowledge-Based Systems
| Hi-index | 0.10 |
This paper presents a new discrete wavelet transform (DWT) based illumination normalization approach for face recognition under varying lighting conditions. Our method consists of three steps. Firstly, DWT-based denoising technique is employed to detect the illumination discontinuities in the detail subbands. And the detail coefficients are updated with using the obtained discontinuity information. Secondly, a smooth version of the input image is obtained by applying the inverse DWT on the updated wavelet coefficients. Finally, multi-scale reflectance model is presented to extract the illumination invariant features. The merit of the proposed method is it can preserve the illumination discontinuities when smoothing image. Thus it can reduce the halo artifacts in the normalized images. Moreover, only one parameter involved and the parameter selection process is simple and computationally fast. Experiments are carried out upon the Yale B and CMU PIE face databases, and the results demonstrate the proposed method can achieve satisfactory recognition rates under varying illumination conditions.