{"id":836,"date":"2014-03-03T01:20:27","date_gmt":"2014-03-03T01:20:27","guid":{"rendered":"https:\/\/www.copyexpress.co.nz\/blog\/?p=836"},"modified":"2021-08-24T23:32:15","modified_gmt":"2021-08-24T23:32:15","slug":"picture-perfect-how-the-get-the-best-of-your-photos-for-marketing-and-printing","status":"publish","type":"post","link":"https:\/\/www.copyexpress.co.nz\/blog\/picture-perfect-how-the-get-the-best-of-your-photos-for-marketing-and-printing\/","title":{"rendered":"Picture Perfect. How the get the best of your photos for marketing and printing"},"content":{"rendered":"\n

Do you know what \u00a0the most common mistake I see when everyday people make up their own marketing material for us to print is? \u00a0Poor quality photos. Photos are a brilliant tool in your marketing toolbox. People are visual animals so we often make snap judgments about a flyer or packaging on the quality of the images they have. How do you avoid bad images? By following a few simple rules which I’ll outline here with examples and suggestions.<\/p>\n\n\n\n

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Resolution Too Low<\/span>
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While we\u2019ve written about this before [link to resolution article] it is still a very common problem. \u00a0It is usually found when someone copies an image from a web site and tried to use it in printed material. \u00a0Your monitor is designed for about 72dpi while printing is 300 or 600 dpi (for more on DPI read here link to DPI<\/a>. \u00a0Scaling the image just makes it blurry or chunky. \u00a0There is not much we can do to fix this other than get a better quality image. \u00a0However – there is one trick that can help (but it is not a \u201csilver bullet\u201d):. Instead of scaling up to the final size open the image in photo editing software and scale\/enlarge it in steps of 2-5% using best or bi-cubic scaling. Keep repeating until the image is the size you want to use it at. The reason why you should do it this way is because the computer finds it easier to guess the missing pixels when it’s 1 in 20, not 1 in 3 (for a more detailed explanation see our DPI article<\/a> . The final image is slightly soft\/fuzzy but it looks better than the standard way.<\/p>\n\n\n\n

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Everything looks foggy\/dull or harsh\/over bright<\/span>
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This\n is a problem with the image’s contrast and brightness. Contrast is the \nrange of brightness and colours over the whole image. With a low \ncontrast, in the images look muddy. With too much contrast the image \nloses the fine shades of colours. When you use photo image software to \nadjust the contrast, you will find a matching slider for brightness too.\n When you adjust an image’s contrast you are adjusting it’s luminance, \nor how you strongly you see the colours in the image, so when adjust \ncontrast you have to adjust the brightness too to keep it clear to see.<\/p>\n\n\n\n

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The background looks good but the people in the front are dark<\/span>
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This\n happens most often when people take photos looking into a source of \nlight. Unless you tell the camera right things it will try to get best \nrange which means you will have people in the front darkened to \ncompensate for their relative over-brightness. You should always shoot \nimages with the main source of light behind or to the side of you, but \nif you can’t or you are given an image like that here’s how to make the \nbest of the bad situation. The first way to fix it is to adjust the \ncontrast and brightness so that the detail of the subject is clear and \naccept that the background is over bright and washed out. The second \nmore advanced way is to use the Magic Wand<\/em> . The Magic Wand is a \nspecial type of select which only selects part of an image by it’s \ncolour. Adjusting how sensitive the wand is you can carefully pick out \nthe area of the foreground you want to fix, then apply the adjustments \nto that highlighted area only.<\/p>\n\n\n\n

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Colours don’t look like they should<\/span>
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The\n human mind is an amazing thing, it will correct what the eye receives \nto match what it thinks it should see. Often when we look at something \nwe think is certain colour but when a camera records it it’s actually \ndifferent. The most common reason is to do with the type of lighting the\n camera is working with and the colour it casts. Colour cast is the \n‘base colour’ of what we think is white light. Old style light bulbs \nhave a yellow cast, modern energy efficient ones have a blue or green \ncast. Light reflected off snow or sea is blue tinted, street lights make\n things green or orange. The light from the sun changes depending on the\n time of day and the weather conditions. Fixing the problem is often \nvery simple. Most image editing software come with an Auto Balance<\/em> or Auto Level<\/em>\n function. Most modern cameras will store all the information about the \nlighting conditions it was working with inside their images and the Auto\n Balance will read that and correct the image to what we accept as \nnormal. You can also find a White Point <\/em> option with some \nsoftware, where you point to a part of the image you know is white and \nthe computer will adjust the rest. If you want to get hands on, you can \nmanually adjust each of the red, green, and blue channels of the image, \nbut that’s outside the scope of this article.<\/p>\n\n\n\n

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The image has lots of fine dots all over it<\/span>
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The three most common sources of noise<\/em>\n , as it is known, can come from a poor quality camera, digital zooming,\n or poor lighting. Cheaper cameras often have electronics which are \nlimited, so shots which are too busy or where there is too much movement\n cause the process to ‘stutter’ causing the dots. Digital zooming is \nwhere the camera enlarges part of the image it sees and uses that to \nmake the photo. Even the best quality camera has problems in low light \nconditions, having to work hard to grab every bit of light it can. The \nsolutions to the problem of noise is to use the Noise Reduction<\/em> \ntools. This function looks at each pixel of an image and all its \nneighbours and adjust them to be closer together in look. You adjust the\n number of pixels it looks at with each check and how much it can adjust\n them to set the amount of reduction over all. It is a trade off as the \nmore you average each pixel the more blurred (overly smooth) it becomes.<\/p>\n\n\n\n

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The image is blurry<\/span>
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Blurring\n has several sources in a photo: when there is movement, the camera is \nfocusing on the wrong part of the scene, there has been too much noise \nreduction. To counteract this problem there is the Sharpen<\/em> tool. \nSharpening an image works by looking at the changes of colour and \nbrightness on the image and adjusting the edges where it changes to make\n it clearer. This process ‘sharpens’ the image but it can only do so \nmuch. If the image is too blurry there is no tool that can fix it.<\/p>\n\n\n\n

Now\n what are the tools to use to fix the problems. There are countless \nnumbers of photo\/image editing tools out there. If you have a digital \ncamera or good quality smart phone, then you’ll have been given photo \nediting software that can handle all the problems I’ve talked about. \nHowever if you to try some other options you can try are:
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