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HIPIE 2 is an internal name for the HP Smartstream Photo
Enhancement Server, robust, scalable, and automatic photo
image enhancement software, customized for photo specialty
workflows fulfilled using Indigo presses. It is designed for 24/7
operation, without human intervention, and is part of HP Indigo's
Smartstream workflow offering. The codename HIPIE stands for
the original "HP Indigo Photo Image Enhancement" name, with
HIPIE 2 being its second version.
With the advent of digital press, photo specialty prints emerged as an important category for commercial print. This
includes photobooks, customized posters, and calendars. These
applications include consumer photographs, which are not as optimized
for print as those professional photographs used in traditional
jobs. Consumer pictures are often too dark or too bright,
not colorful enough, and/or not sharp enough, for instance. As a
result, Print Service Providers that fulfill photo specialty workflows have the need to
improve image quality in addition to keeping a high print quality.
HIPIE 2 is an automatic image enhancement package, which
works as part of a commercial print environment, enhancing each
incoming photograph in a fast and reliable way. It improves
the visual appearance of the photos as they are printed in
photo specialty products, without human intervention. It is commercialized
by HP Indigo as part of their photo quality offering,
and as part of the HP Smartstream workflow offering, under the
name "HP Smartstream Photo Enhancement Server".
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| Image Enhancement
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HIPIE 2's image enhancement is state-of-the-art. We have introduced innovative enhancements, such as 3D boosting and face make-up. Image analysis
modules determine the amount and type of enhancements needed for each individual photograph. The user is able to apply the following image processing tasks. All these tasks are completely automatic, but their strengths
can be influenced by the user controls.
- Sharpening Each input image is sharpened as needed, so
that it appears at the right sharpness in print.
- Noise reduction Noise is estimated, and then reduced,
without damaging texture or fine details in the image.
- 3D boosting This is a novel feature, whereby shadings are
enhanced so to give an impression of increased depth to the
objects in the image (see Fig. 2).
- Contrast enhancement Low-contrasted images have
their effective dynamic-range stretched; this includes lowexposure
images, which are brightened (see Fig. 3).
- Shadow detailing HIPIE 2 detects the low-exposed regions
of the image, and brightens them, without demaging
the well-exposed regions of the image (see Fig. 4).
- Face make-up Another novel feature, this makes sure that
skin on faces are smoothed, as if the subject applied makeup,
reducing the visibility of wrinkles and minor blemishes.
- Chroma boosting HIPIE 2 enhances overall image chromaticity.
- JPEG artifact reduction Blocking and ringing artifacts,
typical from strong JPEG compression, are reduced.
- Face color correction Skin color is analyzed and corrected
for photos with a color cast.
- Resolution Enhancement If the image resolution is too
low, compared to the target print size, then the resolution is
doubled by a smart interpolation algorithm in order to avoid
jagginess or pixelization on edges.
- Red-eye removal Optionally, HIPIE contains a module for
automatically detecting and removing red-eye effects.
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| Example Enhancements
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| Face make-up |
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| Skin color correction |
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| 3D Boosting |
| System Infrastructure
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HIPIE 2 is intended to fit seamlessly into high-throughput
photo specialty workflows, which has a number of implications.
First, it must be robust, meaning that it must be able to run nonstop
for months on end and it must be able to recover automatically
from any possible failures. Second, it must be scalable,
meaning that it must be able to utilize any number of processors
in a distributed computing environment. Third, it must be easy to
configure and manage.
HIPIE 2 uses a master-slave architecture and has five components.
The Windows service is used to (automatically) start
and stop the other components of the system, and there is a
Windows service component on each host in the cluster. Hot
folder processes are responsible for 'watching' each configured
hot folder, and ensuring that each input file is processed appropriately
by a worker process. The queue process matches work
requests from hot folder processes with work offers from worker
processes, thus distributing work from the various hot folders
throughout the cluster to worker processes. The worker processes
simply request work from the queue process, enhance the image
using the options passed as part of the request, and return the completion
status to the requesting hot folder when done. A logger
process per host in the cluster is used to record log messages from
the various components in the system.
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| Publication |
- Automatic Photo Enhancement Server (HIPIE 2)
Renato Keshet, Carl Staelin, Boris Oicherman, Mani Fischer, Pavel Kisilev, Sagi Schein, Doron Shaked, Marie Vans, Hila Nachlieli, Ruth Bergman, Ron Maurer, Michal Aharon, Alex Berkovich, Shimrit Feldman, Ran Waidman, Oren Bengi, Gal Amit, Shlomo Harush, Alon Asher, Matthew Gaubatz, Steven J Simske, Darryl Greig, Hui Chao, International Symposium on Technologies for Digital Fulfillment (TDPF), 2009.
- Perceptual Segmentation: Combining Image Segmentation With Object Tagging
Bergman, R.; Nachlieli, H. (2011). IEEE Transactions on Image Processing (June 1, 2011), 20(6), 1668-1681. DOI: 10.1109/TIP.2010.2088970
- HP Indigo Photo Enhancement Server
Product Description, 2007.
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