I’ve been kicking around the idea of doing a hands-on photography workshop, and I’m curious about how much interest there would be.

When athletes study a sport, they don’t just go out and play. They also do drills to improve some technical aspect of their game. Running through tires improves agility. Batting practice improves, well, batting. (If I was the least bit athletic, I would fill this paragraph with a few more examples to support my point and engage your interest. I’m not, so just imagine I did.)

Similarly, I want to do a workshop of technical photography exercises. This wouldn’t be a class of going to the beach and taking pretty pictures, but rather going somewhere and spending some time working on focused exercises. I make these up for myself and do them, and I find them very helpful in helping me become more technically competent, or in helping me see things in a different way.

Logistics: The workshop would be held on a weekend day somewhere near San Francisco– currently, I’m thinking that either the Alameda Naval Air Station or Treasure Island might be interesting venues, but I’m open to suggestions. My timeframe is sometime in January, 2009. Participants should have some sort of digital camera, for quick review of photos, and a dSLR would be best.  The target audience would be beginning and intermediate photographers, those who have gained basic competence with their camera and want to work on improving their skills.

As this would be an experimental class on my part, the fee would be a small donation to the charity of your choice, and maybe a dollar or two to cover my expenses if I do printed materials to go with it.

Would you be interested? If so, what would you like to get out of such a class? Do you have a suggestion for a location? Is there anything that would make you more or less likely to attend?

This isn’t really about how to take better pictures, but it’s important enough that I want to share.

Yesterday, while walking through San Francisco’s SOMA neighborhood, I spotted a sign in a bookstore window. The sign reminded me of something, so I pulled out my phone and took a picture of it. Just as I finished taking the picture, one of the store’s employees came up to the window and gestured to indicate that I wasn’t allowed to do that.

I didn’t push the issue, but he happened to be dead wrong. In the US, I have every right to photograph the exterior of a commercial building, so long as I am doing so from public property. If I’m on private property, the owners of the property have every right to ask me to refrain from taking photos, and I must do so.

Every photographer should read the following information on photographers’ rights.  It’s even provided as a printable PDF, so that you can keep a copy in your camera bag.  In our current social climate, photographers are being hassled more and more in the name of security, and it’s important to know your rights, responsibilities, and restrictions.

If you’re new to Stop Shooting Auto!, the best way to explore the site is to click the link on the left for exposure lessons in order.  That’s the gentle introduction to exposure that’s the heart of the site.

I got email from a reader this week thanking me for SSA!, and asking what they could do for the site. Thanks for asking! I love getting email like this– it makes me feel like I’m helping people.

First off, I’ll never say no to receiving large stacks of cash. If you have a lot more money than you know what to do with, feel free to come by my loft and leave it in my mailbox. I promise to buy lots of excellent camera gear with it. :-)

Seriously, comments and questions on the entries really contribute a lot to the site. Not only do they help me feel like I’m not shouting into the void, but they also give me excellent feedback. If I know where my explanations have worked and what could be clearer I can do a better job in the future. Suggestions for topics let me know what people are interested in learning about.  Constructive criticism is welcome too, of course.  You can keep the hate mail to yourself, though.

Another great way to help is to spread the word.  Tell your friends!  Link to the site. (It goes without saying, but don’t spam.)   Stop Shooting Auto! is still a young site, and publicity is a good thing.  Getting new readers always makes me happy.

Click the links.  I actually make a very tiny amount of money from the site from Amazon product referral links.  As of this writing, I’ve made less than $50– on an hourly basis, that would make me the envy of third-world sweat shop workers.  Clearly, I’m not doing this to get rich!  However, when you buy something from a product link on the recommendation page or What’s in Patti’s camera bag?, I get a few cents from it.  That won’t make me rich, but it makes me smile.

More than anything, though, keep reading and commenting, and let me know how I’m doing.

In the last couple of lessons I showed you what a histogram is, and talked about what a good histogram looks like for a typical image. I also showed you a few bad-looking histograms for overexposed and underexposed images.

Sometimes, a strange-looking histogram is actually OK. This happens if the image that you’re capturing has an unusual distribution of levels, such as a lot of very light or very dark areas. It can also occur if you have a very narrow range of colors, or several other things that are out of the ordinary.

Look at the histogram above. It doesn’t look at all like a bell curve, but rather has several fairly well-defined peaks. There might be a little bit of clipping on the left and right, but there might also just be some solid black and solid light-color areas. It’s hard to know for sure from the histogram whether the image is well-exposed or not, but because there’s a good distribution across the range I would guess that it’s probably not too far off.

At first glance, this looks like a massively-underexposed image. There’s a huge amount of clipping on the blacks, and what looks like a little bit of clipping of whites as well. On the other hand, it could be an image with fast swaths of black and very dark colors, and a few bright spots.

As luck would have it, both of these images are within shouting distance of being well-exposed.

When we look at the actual images, it’s pretty easy to see why the histograms were weird. The image with spikes has a very distinct color breakdown. I probably could have done a slightly better job with the exposure, but it’s not far off. The image on the right does indeed have vast swaths of black in the form of the night sky and the ground. A few of the highlights are blown out, as we can see at the far right of the histogram, but that’s really hard to avoid when taking pictures of lights against a black background.

What did we learn from this? Well, if I’m any good at all, we’ve learned that you need to consider your subject matter when you’re looking at a histogram and use that to judge what the histogram should look like. I know that sounds impossible, but most of the time it’s actually rather easy to do once you get the hang of it. In fact, here’s one to think about. If you were taking a picture of the full moon at night, what should the histogram look like?

Oh yes. The other day I showed you a histogram with almost all of the pixels left of center and asked what you thought about the exposure. Both Sarah and TJ had excellent things to say about the image, but TJ completely nailed it– “the object… is mostly black.” In fact, it was my black camera bag shot against a dark carpet. There’s a blip at the far right for the embroidery on the logo, but other than that the image is just naturally dark. It was perfectly reasonable to guess that the image was underexposed, but it was sort of a trick question. I’m just mean like that.

Do you feel like you have a good basic understanding of how the histogram works?

In my last entry, I introduced the histogram and described its basic function. I even showed a couple of examples. If you read the entry you should have a good understanding of what a histogram is, but there’s probably a great big question in your mind right now: “What is a good histogram?”

The short answer is that there’s no such thing.

You don’t like that answer much, do you? Nope, me either, so even though I could save myself a bunch of typing I won’t leave it at that. I don’t want people running around saying that I’m a meanie.

The longer answer is that what a good histogram is depends on the subject of your photo. For “typical” images, those with an average range of light and dark areas, a good histogram will basically look like a bell curve that’s centered around the center of the graph. And look! Here’s one now. Isn’t that convenient?

Looking at that histogram, you might conclude that there’s nothing in the image that’s 100% bright white, and a very tiny amount that’s pure black. The photo has a good range of tones from light to dark, and there are more moderately-light pixels than moderately dark ones. Let’s look at the image and see if we’re right.

Hey, we guessed pretty well. The flower has a range of tones from black to nearly-white, and there are pretty big light-colored areas.

Note that the exposure looks pretty good to our eye and on the histogram. There are no areas where it looks like we’ve cut off dark colors and made them black, or lost information because the pixels have become pure white. If we had, you’d see spikes at the left or right side of the histogram.

In general, that’s the mark of a good histogram for a typical, average photo. You generally want the majority of the pixels to be somewhere in the center of the graph, without a lot of stuff piled up on one side or the other. If you’re shooting something that has a significant amount of pure black or pure white in it, you’ll sometimes get a spike on the left or right side. That’s OK, but you’ll probably be OK if most of the pixels are somewhere near the center.

When I shot this flower, I took a bunch of pictures with the lighting changed slightly, and most of them didn’t turn out as good as this one. Let’s look at a couple of bad ones now.

If you’re like me, you’re probably thinking about the three bears right now– “This one is too dark. This one is too light. And this one is juuuussstttt right.” If you look at the bottom right corner of the images, you can see the histograms for them. (Or click for larger versions of the dark and light ones respectively.) The histogram for the dark flower has the whole graph left of center, and there’s a big pile of pixels right up against the left edge.  That means that all of the colors in the image are dark, and the part against the edge shows that there’s a bunch of solid-black pixels.  That’s not good– it means we cut off a bunch of information.

The too-light flower has almost all of its pixels on the right side of the graph, which usually indicates that the image has been overexposed. However, if you look closely you can see that there’s nothing against the right edge of the graph. That’s a good thing– it means that you can probably use an image editing program like Photoshop to fix the image and get something pretty good. The dark image might be recoverable as well, but it will never be as good because some of the information got lost when the picture was taken.

If you’re taking a picture of something that’s mostly black or very bright, or something with a narrow range of brightnesses, a correct histogram may look strange. In my next lesson I’ll show you some examples of those, and answer the question about the all-on-the-left histogram at the bottom of my last entry.

And here’s something for you to practice: get into the habit of looking at your histograms. Take a few pictures, and review them on the camera. Check your manual to see how to view the histogram, but on my Canons I get it by pressing the “Info” button while viewing an image. The best way to get familiar with it– pretty soon you’ll have a good eye for what’s right and wrong.

I confess… I’ve been neglecting Stop Shooting Auto! for a while.  I’ve been traveling constantly for the last couple of months, and that plus a full-time job has kept me quite busy.  In fact, I’m writing this while sitting at SFO while I wait for my delayed flight to take off.

I promised I’d address the histogram next, so let’s do it.

Maybe you’ve seen something that looks like this, either in Photoshop or other image editing software, or on your camera when you reviewed an image.  Maybe you even took a guess at what it is and how it works, and if you did you probably guessed right.  That’s the histogram.

Histogram is a scary, technical-sounding word, but it’s actually a really simple concept.  The histogram is just a graph of how many dark and light pixels there are in your image.  At the far left you’ll see how many dark pixels there are, then moving to the right you’d see count of lighter and lighter pixels until the far right was pure white pixels.

In the histogram above, you can see that there are a very few solid black pixels, lots that are a little bit darker than average, a bunch that are a little lighter than average, and a chunk that are pure white. Let’s look at the image and see what it looks like.

There are a few pure black or very close to black pixels, mostly around the trash can and along the left wall– that’s the tiny hump on the far left.

The pure white pixels are mostly on the sign, in particular the words “San Francisco Marketplace” are pure white, and a tiny bit overexposed.  That’s the vertical bar right along the far right edge.

The dark of the sign, the dark carpet, and the dark part of the wall are the peak on the left. The peak on the right is the lighter part of the walls.

Most histograms that you will see don’t take color into account, only brightness.  That means that a very bright blue will look just like a very bright white.  Some cameras have the ability to do histograms with the colors separate, and of course most postprocessing software can do so as well.

This one is kind of fun. Without seeing the image, what can you tell me about it?  Obviously you can’t tell me what it’s a picture of, but can you make any guesses about what the image looks like?  Is it light or dark?  Does it have lots of different shades or only a few?  Are there any pure black or pure white areas in the image?

Do you think this image is well-exposed, underexposed, or overexposed?

OK, they’re calling my flight now.  Ciao!

Very few people did the April homework assignment, so I’m extending it until the end of May.  Grab your cameras and go capture something in motion!  There’s a prize, of course– a signed Flower Porn print, and two if enough people participate.

If you’re new to Stop Shooting Auto! or you haven’t done so before, you’ll want to start by going through the exposure lessons in order.  That will give you a gentle, beginner-friendly introduction to the principles of exposure and the way your camera’s controls work.  Don’t be afraid to ask questions and leave comments… I love getting them, and I’m happy to answer as many questions as I can.

I promised to write about histograms, but I’ve been pretty busy. However, here’s something quick I wanted to share. I went whale watching today with a couple of friends, and so of course I took the camera along. The thought process that I used here is pretty much my standard way of thinking about what I want to shoot.

Packing the camera bag was easy– the Canon 70-200 f/4L IS was the perfect lens choice, since it was long enough to bring the whales in close, and as a bonus image stabilization would help a little bit with the motion of the boat. Well, maybe, but it couldn’t hurt.

What about settings? I didn’t really care about depth-of-field other than wanting to have enough to get my subject in focus, so I set the camera to aperture priority mode and f/8. I realized that I was going to be shooting moving animals from a moving boat on choppy waters, and so shutter speed would be critical. I set the ISO to 100 and pointed the camera at the water, looked through the viewfinder, and pressed the button halfway to see what the camera would want to do. It picked 1/320 for a shutter speed. Under normal circumstances that would be fast enough, since it was faster than one over the focal length of the lens (1/200 in this case), but with all of that motion I wanted something faster. I took a wild guess and thought that 1/800 was a good minimum.

If I got 1/320 at ISO 100, then at ISO 200 I should be able to shoot 1/640. That still wouldn’t be enough, but at ISO 400 I should be able to shoot 1/1250. (Note: shutter speeds don’t always change in precise multiples of two. It’s confusing until you get used to it.) Since 1/1250 was well above my arbitrarily-chosen 1/800 threshold, ISO 400 should be perfect.

The sky was gray when we left the harbor, but I expected some of the fog to burn off over the course of the trip. I knew that I would have to doublecheck the settings if it started getting sunny– the fastest shutter speed my camera could do was 1/4000, which meant that I only had around two stops of room before my camera would be forced to overexpose the image. Sure enough, the sun came out a few hours later, but I was still able to shoot at around 1/2000. Otherwise, I would have either dropped down to ISO 200 or changed the aperture to f/11.

The thought process for this is one that you should use whenever you pick up a camera. What do I want this image to look like? What range of apertures and shutter speeds will get me the results I want? What camera settings should I use to get the right apertures and shutter speeds? As a novice you won’t always know all of the answers to those questions, but you can start guessing. “Do I want the background blurry or sharp? Do I want to capture or freeze motion?” Just answering those two questions before you pick up the camera will give you a huge leg up in getting the image you want.

Oh, yeah, a quick note about the gull. When I first looked at this picture on the camera’s LCD, I was rather shocked– the image looked blurry! It was taken at a shutter speed of 1/2500, so that hardly seemed possible. Either I’d seriously misjudged what shutter speeds would work, and I didn’t think I had, or something else was amiss. I zoomed in on the image and realized that the fuzziness I thought I was seeing was really the transition in feather colors at the rear edge of the wing. The image was actually so sharp that I could pick out individual feathers quite clearly.

Someone at SFGate.com seems to have done their homework and captured something in motion.   Why haven’t you?

I’ll extend the deadline for a little while, but the challenge is simple– capture something in motion.  Go here for full details of the homework assignment.